| { | |
| "matching": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "matching", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 618272766.36, | |
| "num_examples": 9792, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 34157757.0, | |
| "num_examples": 531, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 29813118.0, | |
| "num_examples": 528, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 594460072, | |
| "dataset_size": 682243641.36, | |
| "size_in_bytes": 1276703713.3600001 | |
| }, | |
| "matching_from_pixels": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "matching_from_pixels", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 101439044.384, | |
| "num_examples": 1632, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 33714551.0, | |
| "num_examples": 531, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 29368704.0, | |
| "num_examples": 528, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 139733134, | |
| "dataset_size": 164522299.384, | |
| "size_in_bytes": 304255433.384 | |
| }, | |
| "ranking": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "winner_source": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "ranking", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 594615535.632, | |
| "num_examples": 9576, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 32624105.0, | |
| "num_examples": 507, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 28907567.0, | |
| "num_examples": 513, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 571604579, | |
| "dataset_size": 656147207.632, | |
| "size_in_bytes": 1227751786.632 | |
| }, | |
| "ranking_from_pixels": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "winner_source": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "ranking_from_pixels", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 101282973.752, | |
| "num_examples": 1596, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 32072331.0, | |
| "num_examples": 506, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 28550057.0, | |
| "num_examples": 513, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 134283256, | |
| "dataset_size": 161905361.752, | |
| "size_in_bytes": 296188617.752 | |
| }, | |
| "explanation": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "explanation", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 133827514.64, | |
| "num_examples": 2340, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 8039885.0, | |
| "num_examples": 130, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 6863533.0, | |
| "num_examples": 131, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 139737042, | |
| "dataset_size": 148730932.64, | |
| "size_in_bytes": 288467974.64 | |
| }, | |
| "explanation_from_pixels": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "explanation_from_pixels", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 23039316.0, | |
| "num_examples": 390, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 7956182.0, | |
| "num_examples": 130, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 6778892.0, | |
| "num_examples": 131, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 37552582, | |
| "dataset_size": 37774390.0, | |
| "size_in_bytes": 75326972.0 | |
| }, | |
| "matching_1": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "matching_1", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 593200158.116, | |
| "num_examples": 9684, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 36712942.0, | |
| "num_examples": 546, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 34157757.0, | |
| "num_examples": 531, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 563587231, | |
| "dataset_size": 664070857.116, | |
| "size_in_bytes": 1227658088.1160002 | |
| }, | |
| "matching_from_pixels_1": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "matching_from_pixels_1", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 94090646.83, | |
| "num_examples": 1614, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 36257141.0, | |
| "num_examples": 546, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 33714551.0, | |
| "num_examples": 531, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 137278691, | |
| "dataset_size": 164062338.82999998, | |
| "size_in_bytes": 301341029.83 | |
| }, | |
| "ranking_1": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "winner_source": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "ranking_1", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 580099188.9, | |
| "num_examples": 9450, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 35332200.0, | |
| "num_examples": 534, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 32624105.0, | |
| "num_examples": 507, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 546559254, | |
| "dataset_size": 648055493.9, | |
| "size_in_bytes": 1194614747.9 | |
| }, | |
| "ranking_from_pixels_1": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "winner_source": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "ranking_from_pixels_1", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 93123370.15, | |
| "num_examples": 1575, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 34965110.0, | |
| "num_examples": 534, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 32072331.0, | |
| "num_examples": 506, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 130879365, | |
| "dataset_size": 160160811.15, | |
| "size_in_bytes": 291040176.15 | |
| }, | |
| "explanation_1": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "explanation_1", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 136614332.45999998, | |
| "num_examples": 2358, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 7911995.0, | |
| "num_examples": 128, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 8039885.0, | |
| "num_examples": 130, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 134637839, | |
| "dataset_size": 152566212.45999998, | |
| "size_in_bytes": 287204051.46 | |
| }, | |
| "explanation_from_pixels_1": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "explanation_from_pixels_1", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 21986652.0, | |
| "num_examples": 393, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 7831556.0, | |
| "num_examples": 128, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 7956182.0, | |
| "num_examples": 130, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 37534409, | |
| "dataset_size": 37774390.0, | |
| "size_in_bytes": 75308799.0 | |
| }, | |
| "matching_2": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "matching_2", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 591676321.09, | |
| "num_examples": 9630, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 33697178.0, | |
| "num_examples": 540, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 36712942.0, | |
| "num_examples": 546, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 571864348, | |
| "dataset_size": 662086441.09, | |
| "size_in_bytes": 1233950789.0900002 | |
| }, | |
| "matching_from_pixels_2": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "_type": "Sequence" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "newyorker_caption_contest", | |
| "dataset_name": "newyorker_caption_contest", | |
| "config_name": "matching_from_pixels_2", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 96253584.505, | |
| "num_examples": 1605, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 33236000.0, | |
| "num_examples": 540, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 36257141.0, | |
| "num_examples": 546, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 137890850, | |
| "dataset_size": 165746725.505, | |
| "size_in_bytes": 303637575.505 | |
| }, | |
| "ranking_2": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "winner_source": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "ranking_2", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 10183446, | |
| "num_examples": 9306, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 551023, | |
| "num_examples": 531, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 544050, | |
| "num_examples": 534, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_2.zip": { | |
| "num_bytes": 2380230, | |
| "checksum": "e125304613056eeda04690bb68b50921ea9871ca299f37c95f61624fd74fdafb" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 41903439, | |
| "post_processing_size": null, | |
| "dataset_size": 11278519, | |
| "size_in_bytes": 53181958 | |
| }, | |
| "ranking_from_pixels_2": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "winner_source": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "ranking_from_pixels_2", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 514484, | |
| "num_examples": 1550, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 177286, | |
| "num_examples": 531, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 176960, | |
| "num_examples": 534, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels_2.zip": { | |
| "num_bytes": 203718, | |
| "checksum": "2949692ace6eb2162fffaff17a88898d2d608dcfdc2d04861c23ec05b87ef6c5" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 39726927, | |
| "post_processing_size": null, | |
| "dataset_size": 868730, | |
| "size_in_bytes": 40595657 | |
| }, | |
| "explanation_2": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "explanation_2", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 3074106, | |
| "num_examples": 2346, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 163651, | |
| "num_examples": 132, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 158658, | |
| "num_examples": 128, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_2.zip": { | |
| "num_bytes": 861915, | |
| "checksum": "14ed5f81c51718486b10716cf9f714c756bdf0c89e50bb958c16a58b1ea09320" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 40385124, | |
| "post_processing_size": null, | |
| "dataset_size": 3396415, | |
| "size_in_bytes": 43781539 | |
| }, | |
| "explanation_from_pixels_2": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "explanation_from_pixels_2", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 232956, | |
| "num_examples": 391, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 79386, | |
| "num_examples": 132, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 78219, | |
| "num_examples": 128, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_from_pixels_2.zip": { | |
| "num_bytes": 122669, | |
| "checksum": "e51447c1c4a760d47c0c647fc203d96295ae06ad87166c3a6db383eaa3f7e78e" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 39645878, | |
| "post_processing_size": null, | |
| "dataset_size": 390561, | |
| "size_in_bytes": 40036439 | |
| }, | |
| "matching_3": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "matching_3", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 13262428, | |
| "num_examples": 9630, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 706095, | |
| "num_examples": 546, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 714032, | |
| "num_examples": 540, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_3.zip": { | |
| "num_bytes": 3307856, | |
| "checksum": "21f934f5b7db7864856878346c1a30112dbe479a594e42db2867c88e5cfe2a57" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 42831065, | |
| "post_processing_size": null, | |
| "dataset_size": 14682555, | |
| "size_in_bytes": 57513620 | |
| }, | |
| "matching_from_pixels_3": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "matching_from_pixels_3", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 740655, | |
| "num_examples": 1605, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 256896, | |
| "num_examples": 546, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 252854, | |
| "num_examples": 540, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_from_pixels_3.zip": { | |
| "num_bytes": 308596, | |
| "checksum": "8e30f3c272550883e989fa36f0957b860b38a689dea3d6ea2fed71403feddeca" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 39831805, | |
| "post_processing_size": null, | |
| "dataset_size": 1250405, | |
| "size_in_bytes": 41082210 | |
| }, | |
| "ranking_3": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "winner_source": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "ranking_3", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 10257068, | |
| "num_examples": 9324, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 531455, | |
| "num_examples": 531, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 551023, | |
| "num_examples": 531, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_3.zip": { | |
| "num_bytes": 2390643, | |
| "checksum": "f2f65f144fa70b0717b7c05efc7926e9fdbfb96f946f7ad2eb8ca4ff248826dc" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 41913852, | |
| "post_processing_size": null, | |
| "dataset_size": 11339546, | |
| "size_in_bytes": 53253398 | |
| }, | |
| "ranking_from_pixels_3": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "winner_source": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "ranking_from_pixels_3", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 513986, | |
| "num_examples": 1553, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 177459, | |
| "num_examples": 531, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 177286, | |
| "num_examples": 531, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels_3.zip": { | |
| "num_bytes": 203557, | |
| "checksum": "80b1f658c19dd021f7f3f357cc39a643ec1683a022e2c81e7db2eef458824468" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 39726766, | |
| "post_processing_size": null, | |
| "dataset_size": 868731, | |
| "size_in_bytes": 40595497 | |
| }, | |
| "explanation_3": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "explanation_3", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 3072628, | |
| "num_examples": 2334, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 158611, | |
| "num_examples": 130, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 163651, | |
| "num_examples": 132, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_3.zip": { | |
| "num_bytes": 860977, | |
| "checksum": "0d09e7c18ac10259f5fc0a7e79bdb2ead04debf8ce65d1da1b90f721cc6daaad" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 40384186, | |
| "post_processing_size": null, | |
| "dataset_size": 3394890, | |
| "size_in_bytes": 43779076 | |
| }, | |
| "explanation_from_pixels_3": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "explanation_from_pixels_3", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 232949, | |
| "num_examples": 389, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 78227, | |
| "num_examples": 130, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 79386, | |
| "num_examples": 132, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_from_pixels_3.zip": { | |
| "num_bytes": 123039, | |
| "checksum": "6aee346705346f7ccc46adccfa89882847744b77b882825364dca0b16a0cf94a" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 39646248, | |
| "post_processing_size": null, | |
| "dataset_size": 390562, | |
| "size_in_bytes": 40036810 | |
| }, | |
| "matching_4": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "matching_4", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 13402726, | |
| "num_examples": 9702, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 687942, | |
| "num_examples": 528, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 706095, | |
| "num_examples": 546, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_4.zip": { | |
| "num_bytes": 3339066, | |
| "checksum": "3f8f072087ba28a0a49c4ed068eef17dd41f8737a7f690c850c36efcb3d6441e" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 42862275, | |
| "post_processing_size": null, | |
| "dataset_size": 14796763, | |
| "size_in_bytes": 57659038 | |
| }, | |
| "matching_from_pixels_4": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "matching_from_pixels_4", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 749981, | |
| "num_examples": 1617, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 243528, | |
| "num_examples": 528, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 256896, | |
| "num_examples": 546, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_from_pixels_4.zip": { | |
| "num_bytes": 307932, | |
| "checksum": "cecbce805b551669534abb39e49f5fc8cac2d8b3a84d48555db19bc01992b2dd" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 39831141, | |
| "post_processing_size": null, | |
| "dataset_size": 1250405, | |
| "size_in_bytes": 41081546 | |
| }, | |
| "ranking_4": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "winner_source": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "ranking_4", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 10382406, | |
| "num_examples": 9432, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 527159, | |
| "num_examples": 513, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 531455, | |
| "num_examples": 531, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_4.zip": { | |
| "num_bytes": 2413757, | |
| "checksum": "b3cf071c6046ece7c7a4dd1fb430a7cad8debdebfdcc7c7b2b6efb40fd0d4cfa" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 41936966, | |
| "post_processing_size": null, | |
| "dataset_size": 11441020, | |
| "size_in_bytes": 53377986 | |
| }, | |
| "ranking_from_pixels_4": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "winner_source": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "ranking_from_pixels_4", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 521623, | |
| "num_examples": 1571, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 169649, | |
| "num_examples": 513, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 177459, | |
| "num_examples": 531, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels_4.zip": { | |
| "num_bytes": 203752, | |
| "checksum": "79e83d153f410977e4cac58fc870ca0d9f8ae6e4748bfa21426dc57d66efd437" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 39726961, | |
| "post_processing_size": null, | |
| "dataset_size": 868731, | |
| "size_in_bytes": 40595692 | |
| }, | |
| "explanation_4": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_location": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "image_uncanny_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "entities": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "questions": { | |
| "feature": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "length": -1, | |
| "id": null, | |
| "_type": "Sequence" | |
| }, | |
| "caption_choices": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "from_description": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "explanation_4", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 3084810, | |
| "num_examples": 2340, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 162089, | |
| "num_examples": 131, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 158611, | |
| "num_examples": 130, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_4.zip": { | |
| "num_bytes": 861773, | |
| "checksum": "f5fcf62641a6c844a56ec0a79ec981977442535f197f9c407c3eb7c1a320252d" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 40384982, | |
| "post_processing_size": null, | |
| "dataset_size": 3405510, | |
| "size_in_bytes": 43790492 | |
| }, | |
| "explanation_from_pixels_4": { | |
| "description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", | |
| "citation": "@article{hessel2022androids,\n title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n journal={arXiv preprint arXiv:2209.06293},\n year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n author={Jain, Lalit and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n year={2020},\n url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n author = \"Radev, Dragomir and\n Stent, Amanda and\n Tetreault, Joel and\n Pappu, Aasish and\n Iliakopoulou, Aikaterini and\n Chanfreau, Agustin and\n de Juan, Paloma and\n Vallmitjana, Jordi and\n Jaimes, Alejandro and\n Jha, Rahul and\n Mankoff, Robert\",\n booktitle = \"LREC\",\n year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n title={Inside jokes: Identifying humorous cartoon captions},\n author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n booktitle={KDD},\n year={2015},\n}\n", | |
| "homepage": "www.capcon.dev", | |
| "license": "", | |
| "features": { | |
| "image": { | |
| "decode": true, | |
| "id": null, | |
| "_type": "Image" | |
| }, | |
| "contest_number": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "caption_choices": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "label": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "n_tokens_label": { | |
| "dtype": "int32", | |
| "id": null, | |
| "_type": "Value" | |
| }, | |
| "instance_id": { | |
| "dtype": "string", | |
| "id": null, | |
| "_type": "Value" | |
| } | |
| }, | |
| "post_processed": null, | |
| "supervised_keys": null, | |
| "task_templates": null, | |
| "builder_name": "newyorker_caption_contest", | |
| "config_name": "explanation_from_pixels_4", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "description": null, | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 234887, | |
| "num_examples": 390, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 77448, | |
| "num_examples": 131, | |
| "dataset_name": "newyorker_caption_contest" | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 78227, | |
| "num_examples": 130, | |
| "dataset_name": "newyorker_caption_contest" | |
| } | |
| }, | |
| "download_checksums": { | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_from_pixels_4.zip": { | |
| "num_bytes": 122706, | |
| "checksum": "8877b0cba778dfb76a9374a9b5036f1a2665c65023dc3ca5640be899c85fd135" | |
| }, | |
| "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": { | |
| "num_bytes": 39523209, | |
| "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748" | |
| } | |
| }, | |
| "download_size": 39645915, | |
| "post_processing_size": null, | |
| "dataset_size": 390562, | |
| "size_in_bytes": 40036477 | |
| } | |
| } |