Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension
Paper
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2002.00293
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Published
UCL NLP
university
AI & ML interests
Language models, reasoning, robustness, question answering, evaluation, theorem proving, knowledge graphs, mechanistic interpretability, adversarial training, dynamic adversarial data collection, in-context learning, natural language explanations, safety and security, self-training, knowledge distillation, natural language processing
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mbartolo
authored
9
papers
8 months ago
Interpretation of Natural Language Rules in Conversational Machine Reading
Paper
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1809.01494
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Published
Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality
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2204.03162
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Published
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1
Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation
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2104.08678
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Published
Dynatask: A Framework for Creating Dynamic AI Benchmark Tasks
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2204.01906
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Published
Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants
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2112.09062
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Published
DMLR: Data-centric Machine Learning Research -- Past, Present and Future
Paper
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2311.13028
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Published
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1
Human Feedback is not Gold Standard
Paper
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2309.16349
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Published
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5
The PRISM Alignment Project: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models
Paper
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2404.16019
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Published
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1
mbartolo
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a
paper
11 months ago
mbartolo
updated
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11 months ago