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Co-authored-by: Niels Rogge <[email protected]>

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@@ -393,4 +393,48 @@ Reproduction script: https://huggingface.co/infgrad/dewey_en_beta/blob/main/scri
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  | [voyage-3](https://blog.voyageai.com/2024/09/18/voyage-3/) | 100% | Unknown | 1024 | 32000 | 74.06 | 74.06 | 74.06 |
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  | [inf-retriever-v1](https://huggingface.co/infly/inf-retriever-v1) | 100% | 7B | 3584 | 32768 | 73.19 | 73.19 | 73.19 |
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- ### 3.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  | [voyage-3](https://blog.voyageai.com/2024/09/18/voyage-3/) | 100% | Unknown | 1024 | 32000 | 74.06 | 74.06 | 74.06 |
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  | [inf-retriever-v1](https://huggingface.co/infly/inf-retriever-v1) | 100% | 7B | 3584 | 32768 | 73.19 | 73.19 | 73.19 |
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+ ### 3.3 LoCoV1
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+
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+ URL: https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries\
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+ https://huggingface.co/datasets/hazyresearch/LoCoV1-Documents
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+
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+ Reproduction script: https://huggingface.co/infgrad/dewey_en_beta/blob/main/scripts/evaluate/run_evaluate_loco.py
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+
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+ Metric: NDCG@10
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+
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+ Result:
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+ | **dataset-name** | **bge-m3-8k** | **gte-modernbert-base-8k** | **Linq-Embed-Mistral-4k** | **Linq-Embed-Mistral-8k** | **SFR-Embedding-Mistral-8k** | **e5-mistral-7b-instruct-8k** | **dewey_en_beta-8k** | **dewey_en_beta_64k** | **dewey_en_beta_64k-multi-vectors** |
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+ |:---------------------------------:|:-------------:|:--------------------------:|:-------------------------:|:-------------------------:|:----------------------------:|:-----------------------------:|:--------------------:|:------------------------:|:--------------------------------------:|
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+ | **2wikimqa_test** | 0.9271 | 0.8658 | 0.8884 | 0.9067 | 0.8965 | 0.8901 | 0.8953 | 0.9051 | 0.9775 |
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+ | **courtlistener_HTML_test** | 0.1933 | 0.2349 | 0.3551 | 0.3670 | 0.3647 | 0.3543 | 0.3415 | 0.3616 | 0.4775 |
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+ | **courtlistener_Plain_Text_test** | 0.1888 | 0.2478 | 0.3675 | 0.3761 | 0.3679 | 0.3579 | 0.3377 | 0.3485 | 0.4426 |
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+ | **gov_report_test** | 0.9869 | 0.9750 | 0.9832 | 0.9837 | 0.9816 | 0.9823 | 0.9855 | 0.9883 | 0.9853 |
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+ | **legal_case_reports_test** | 0.3702 | 0.4476 | 0.5398 | 0.5432 | 0.5319 | 0.4850 | 0.5474 | 0.5875 | 0.6534 |
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+ | **multifieldqa_test** | 0.9373 | 0.9341 | 0.9345 | 0.9327 | 0.9450 | 0.9321 | 0.9687 | 0.9564 | 0.9754 |
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+ | **passage_retrieval_test** | 0.4493 | 0.5271 | 0.3470 | 0.3407 | 0.2902 | 0.3248 | 0.7562 | 0.7389 | 0.8550 |
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+ | **qasper_abstract_test** | 1.0000 | 0.9806 | 0.9982 | 0.9982 | 0.9973 | 0.9965 | 0.9973 | 0.9982 | 0.9982 |
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+ | **qasper_title_test** | 0.9860 | 0.8892 | 0.9838 | 0.9833 | 0.9861 | 0.9812 | 0.9742 | 0.9742 | 0.9840 |
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+ | **qmsum_test** | 0.6668 | 0.6307 | 0.6816 | 0.7237 | 0.7169 | 0.7148 | 0.7438 | 0.7613 | 0.8154 |
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+ | **stackoverflow_test** | 0.9634 | 0.9087 | 0.9760 | 0.9760 | 0.9766 | 0.9690 | 0.9362 | 0.9369 | 0.9443 |
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+ | **summ_screen_fd_test** | 0.9320 | 0.9379 | 0.9747 | 0.9635 | 0.9656 | 0.9580 | 0.9796 | 0.9821 | 0.9788 |
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+ | **Average** | 0.7168 | 0.7150 | 0.7525 | 0.7579 | 0.7517 | 0.7455 | 0.7886 |**0.7949** |**0.8406** |
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+
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+ ## 4 Limitations
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+
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+ - Only English text.
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+ - On short text tasks, the performance might not be as good as that of conventional short text embedding models.
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+ - As said before, this model is still in alpha or beta stage, the model may have some unexpected behaviour.
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+
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+ ## 5 Cite
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+
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+ ```
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+ @misc{zhang2025deweylongcontextembedding,
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+ title={Dewey Long Context Embedding Model: A Technical Report},
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+ author={Dun Zhang and Panxiang Zou and Yudong Zhou},
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+ year={2025},
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+ eprint={2503.20376},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.IR},
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+ url={https://arxiv.org/abs/2503.20376},
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+ }