Neural Network Acceptability Judgments von Warstadt, Alex, Singh, Amanpreet, Bowman, Samuel R.

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BLiMP: The Benchmark of Linguistic Minimal Pairs for English von Warstadt, Alex, Parrish, Alicia, Liu, Haokun, Mohananey, Anhad, Peng, Wei, Wang, Sheng-Fu, Bowman, Samuel R.

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Do latent tree learning models identify meaningful structure in sentences? von Williams, Adina, Drozdov, Andrew, Bowman, Samuel R.

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Erratum: “BLiMP: The Benchmark of Linguistic Minimal Pairs for English” von Warstadt, Alex, Parrish, Alicia, Liu, Haokun, Mohananey, Anhad, Peng, Wei, Wang, Sheng-Fu, Bowman, Samuel R.

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Eight Things to Know about Large Language Models von Bowman, Samuel R

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The Dangers of Underclaiming: Reasons for Caution When Reporting How NLP Systems Fail von Bowman, Samuel R

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Let's Think Dot by Dot: Hidden Computation in Transformer Language Models von Pfau, Jacob, Merrill, William, Bowman, Samuel R

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LLM Evaluators Recognize and Favor Their Own Generations von Panickssery, Arjun, Bowman, Samuel R, Feng, Shi

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What Artificial Neural Networks Can Tell Us About Human Language Acquisition von Warstadt, Alex, Bowman, Samuel R

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Spontaneous Reward Hacking in Iterative Self-Refinement von Pan, Jane, He, He, Bowman, Samuel R, Feng, Shi

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Eight Things to Know about Large Language Models von Bowman, Samuel R

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Can neural networks acquire a structural bias from raw linguistic data? von Warstadt, Alex, Bowman, Samuel R

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Clean or Annotate: How to Spend a Limited Data Collection Budget von Chen, Derek, Yu, Zhou, Bowman, Samuel R

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ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context Learning von She, Jingyuan Selena, Potts, Christopher, Bowman, Samuel R, Geiger, Atticus

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Fine-Tuned Transformers Show Clusters of Similar Representations Across Layers von Phang, Jason, Liu, Haokun, Bowman, Samuel R

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What Artificial Neural Networks Can Tell Us About Human Language Acquisition von Warstadt, Alex, Bowman, Samuel R

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Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting von Turpin, Miles, Michael, Julian, Perez, Ethan, Bowman, Samuel R

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The Dangers of Underclaiming: Reasons for Caution When Reporting How NLP Systems Fail von Bowman, Samuel R

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(QA)$^2$: Question Answering with Questionable Assumptions von Kim, Najoung, Htut, Phu Mon, Bowman, Samuel R, Petty, Jackson

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What Will it Take to Fix Benchmarking in Natural Language Understanding? von Bowman, Samuel R, Dahl, George E

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