---
title: "Samuel R. Bowman — all works — Elamur Research"
description: "All 119 works of Samuel R. Bowman in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/samuel-r-bowman/works/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/samuel-r-bowman/works/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Samuel R. Bowman](https://md.research.elamur.ai/free/en/authors/samuel-r-bowman/) / all works

# Samuel R. Bowman — all works

119 works · page 1 of 2 · 1–100 · [← Samuel R. Bowman](https://md.research.elamur.ai/free/en/authors/samuel-r-bowman/)

**1** [2](https://md.research.elamur.ai/free/en/authors/samuel-r-bowman/works/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/samuel-r-bowman/works/page/2/)

1. **[GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/wang-2018-glue-multi-task-benchmark-analysis/) [EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/emnlp-workshop-blackboxnlp-analyzing-and-interpreting-neural-networks-for-nlp/)**Alex Wang, Amanpreet Singh, Julian Michael, et al.*2018 · 7,276 citations*
2. **[A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference](https://md.research.elamur.ai/free/en/papers/williams-2018-broad-coverage-challenge-corpus-sentence/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Adina Williams, Nikita Nangia, Samuel R. Bowman*2018 · 5,551 citations*
3. **[A large annotated corpus for learning natural language inference](https://md.research.elamur.ai/free/en/papers/bowman-2015-large-annotated-corpus-learning-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Samuel R. Bowman, Gabor Angeli, Christopher Potts, et al.*2015 · 5,299 citations*
4. **[Generating Sentences from a Continuous Space](https://md.research.elamur.ai/free/en/papers/bowman-2016-generating-sentences-continuous-space/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al.*2016 · 2,435 citations*
5. [**SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems arXiv:1905.00537**Alex Wang, Yada Pruksachatkun, Nikita Nangia, et al.*2019 · 2,227 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-superglue-stickier-benchmark-general-purpose/)
6. **[XNLI: Evaluating Cross-lingual Sentence Representations ↗](https://aclanthology.org/D18-1269/) Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yet**Alexis Conneau et al.*2018 · 1,885 citations*
7. **[Neural Network Acceptability Judgments ↗](https://doi.org/10.1162/tacl_a_00290) Transactions of the ACL 7: 625–641 (2019) · no summary yet**Alex Warstadt, Amanpreet Singh, Samuel R. Bowman*2019 · 1,765 citations*
8. **[Annotation Artifacts in Natural Language Inference Data](https://md.research.elamur.ai/free/en/papers/gururangan-2018-annotation-artifacts-natural-language-inference/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Suchin Gururangan, Swabha Swayamdipta, Omer Levy, et al.*2018 · 1,615 citations*
9. [**GPQA: A Graduate-Level Google-Proof Q&A Benchmark arXiv:2311.12022**David Rein, Betty Li Hou, Asa Cooper Stickland, et al.*2023 · 1,018 citations*](https://md.research.elamur.ai/free/en/papers/rein-2023-gpqa-graduate-level-google-proof/)
10. **[CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models](https://md.research.elamur.ai/free/en/papers/nangia-2020-crows-pairs-challenge-dataset-measuring/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nikita Nangia, Clara Vania, Rasika Bhalerao, et al.*2020 · 897 citations*
11. **[Language Models (Mostly) Know What They Know ↗](https://arxiv.org/abs/2207.05221) arXiv:2207.05221 · no summary yet**Saurav Kadavath et al.*2022 · 827 citations*
12. **[On Measuring Social Biases in Sentence Encoders](https://md.research.elamur.ai/free/en/papers/may-2019-measuring-social-biases-sentence-encoders/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chandler May, Alex Wang, Shikha Bordia, et al.*2019 · 769 citations*
13. [**What do you learn from context? Probing for sentence structure in contextualized word representations arXiv:1905.06316**Ian Tenney, Patrick Xia, Berlin Chen, et al.*2019 · 602 citations*](https://md.research.elamur.ai/free/en/papers/tenney-2019-learn-context-probing-sentence-structure/)
14. **[Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting](https://md.research.elamur.ai/free/en/papers/turpin-2023-language-models-don-t-always/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Miles Turpin, Julian Michael, Ethan Perez, et al.*2023 · 586 citations*
15. [**Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks arXiv:1811.01088**Jason Phang, Thibault Févry, Samuel R. Bowman*2018 · 503 citations*](https://md.research.elamur.ai/free/en/papers/phang-2018-sentence-encoders-stilts-supplementary-training/)
16. **[BBQ: A hand-built bias benchmark for question answering](https://md.research.elamur.ai/free/en/papers/parrish-2022-bbq-hand-built-bias-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alicia Parrish, Angelica Chen, Nikita Nangia, et al.*2022 · 497 citations*
17. [**Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned arXiv:2209.07858**Deep Ganguli, Liane Lovitt, Jackson Kernion, et al.*2022 · 485 citations*](https://md.research.elamur.ai/free/en/papers/ganguli-2022-red-teaming-language-models-reduce/)
18. **[A Gold Standard Dependency Corpus for English ↗](https://aclanthology.org/L14-1067/) Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14) · no summary yet**Natalia Silveira et al.*2014 · 418 citations*
19. [**Towards Understanding Sycophancy in Language Models arXiv:2310.13548**Mrinank Sharma, Meg Tong, Tomasz Korbak, et al.*2023 · 384 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2023-towards-understanding-sycophancy-language-models/)
20. [**Identifying and Reducing Gender Bias in Word-Level Language Models arXiv:1904.03035**Shikha Bordia, Samuel R. Bowman*2019 · 367 citations*](https://md.research.elamur.ai/free/en/papers/bordia-2019-identifying-reducing-gender-bias-word/)
21. **[A Fast Unified Model for Parsing and Sentence Understanding ↗](https://aclanthology.org/P16-1139/) Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Samuel R. Bowman et al.*2016 · 323 citations*
22. **[Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?](https://md.research.elamur.ai/free/en/papers/pruksachatkun-2020-intermediate-task-transfer-learning-pretrained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yada Pruksachatkun, Jason Phang, Haokun Liu, et al.*2020 · 281 citations*
23. **[LLM Evaluators Recognize and Favor Their Own Generations ↗](https://arxiv.org/abs/2404.13076) arXiv:2404.13076 · no summary yet**Arjun Panickssery, Samuel R. Bowman, Shi Feng*2024 · 212 citations*
24. **[What Will it Take to Fix Benchmarking in Natural Language Understanding? ↗](https://aclanthology.org/2021.naacl-main.385/) Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yet**Samuel R. Bowman, George Dahl*2021 · 204 citations*
25. **[Learning Which Features Matter: RoBERTa Acquires a Preference for Linguistic Generalizations (Eventually) ↗](https://aclanthology.org/2020.emnlp-main.16/) Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yet**Alex Warstadt et al.*2020 · 187 citations*
26. **[Language Modeling Teaches You More than Translation Does: Lessons Learned Through Auxiliary Syntactic Task Analysis ↗](https://aclanthology.org/W18-5448/) Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP · no summary yet**Kelly Zhang, Samuel R. Bowman*2018 · 178 citations*
27. [**What Artificial Neural Networks Can Tell Us About Human Language Acquisition arXiv:2208.07998**Alex Warstadt, Samuel R. Bowman*2022 · 177 citations*](https://md.research.elamur.ai/free/en/papers/warstadt-2022-artificial-neural-networks-tell-us/)
28. **[When Do You Need Billions of Words of Pretraining Data? ↗](https://aclanthology.org/2021.acl-long.90/) Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · no summary yet**Yian Zhang et al.*2021 · 176 citations*
29. **[Do Attention Heads in BERT Track Syntactic Dependencies? ↗](https://arxiv.org/abs/1911.12246) arXiv (Cornell University) · no summary yet**Phu Mon Htut et al.*2019 · 175 citations*
30. **[QuALITY: Question Answering with Long Input Texts, Yes!](https://md.research.elamur.ai/free/en/papers/pang-2022-quality-question-answering-long-input/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, et al.*2022 · 167 citations*
31. **[Recursive Neural Networks Can Learn Logical Semantics ↗](https://aclanthology.org/W15-4002/) Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality · no summary yet**Samuel R. Bowman, Christopher Potts, Christopher D. Manning*2015 · 167 citations*
32. **[Probing What Different NLP Tasks Teach Machines about Function Word Comprehension](https://md.research.elamur.ai/free/en/papers/kim-2019-probing-what-different-nlp-tasks/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Najoung Kim, Roma Patel, Adam Poliak, et al.*2019 · 163 citations*
33. **[Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling ↗](https://aclanthology.org/P19-1439/) Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yet**Alex Wang et al.*2019 · 154 citations*
34. **[Do latent tree learning models identify meaningful structure in sentences?](https://md.research.elamur.ai/free/en/papers/williams-2018-do-latent-tree-learning-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Adina Williams, Andrew Drozdov, Samuel R. Bowman*2018 · 149 citations*
35. **[Eight Things to Know about Large Language Models ↗](https://doi.org/10.1215/2834703x-11556011) Critical AI · no summary yet**Samuel R. Bowman*2024 · 148 citations*
36. **[Instruction Induction: From Few Examples to Natural Language Task Descriptions](https://md.research.elamur.ai/free/en/papers/honovich-2022-instruction-induction-few-examples-natural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Or Honovich, Uri Shaham, Samuel R. Bowman, et al.*2022 · 148 citations*
37. **[Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning ↗](https://arxiv.org/abs/1705.00557) arXiv (Cornell University) · no summary yet**Yacine Jernite, Samuel R. Bowman, David A. Sontag*2017 · 142 citations*
38. **[The RepEval 2017 Shared Task: Multi-Genre Natural Language Inference with Sentence Representations](https://md.research.elamur.ai/free/en/papers/nangia-2017-repeval-2017-shared-task-multi/) [Workshop on Evaluating Vector Space Representations for NLP](https://md.research.elamur.ai/free/en/venues/workshop-on-evaluating-vector-space-representations-for-nlp/)**Nikita Nangia, Adina Williams, Angeliki Lazaridou, et al.*2017 · 128 citations*
39. [**Pretraining Language Models with Human Preferences arXiv:2302.08582**Tomasz Korbak, Kejian Shi, Angelica Chen, et al.*2023 · 121 citations*](https://md.research.elamur.ai/free/en/papers/korbak-2023-pretraining-language-models-human-preferences/)
40. [**Measuring Progress on Scalable Oversight for Large Language Models arXiv:2211.03540**Samuel R. Bowman, Jeeyoon Hyun, Ethan Perez, et al.*2022 · 117 citations*](https://md.research.elamur.ai/free/en/papers/bowman-2022-measuring-progress-scalable-oversight-large/)
41. **[Idiosyncratically Transparent Vowels in Kazakh ↗](https://doi.org/10.3765/amp.v1i1.24) Proceedings of the Annual Meetings on Phonology · no summary yet**Samuel R. Bowman, Benjamin Lokshin*2014 · 109 citations*
42. [**Reasoning Models Don't Always Say What They Think arXiv:2505.05410**Yanda Chen, Joe Benton, Ansh Radhakrishnan, et al.*2025 · 106 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-reasoning-models-don-t-always/)
43. [**Debating with More Persuasive LLMs Leads to More Truthful Answers arXiv:2402.06782**Akbir Khan, John Hughes, Dan Valentine, et al.*2024 · 101 citations*](https://md.research.elamur.ai/free/en/papers/khan-2024-debating-more-persuasive-llms-leads/)
44. **[ListOps: A Diagnostic Dataset for Latent Tree Learning ↗](https://aclanthology.org/N18-4013/) Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop · no summary yet**Nikita Nangia, Samuel R. Bowman*2018 · 96 citations*
45. **[jiant: A Software Toolkit for Research on General-Purpose Text Understanding Models ↗](https://aclanthology.org/2020.acl-demos.15/) Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations · no summary yet**Yada Pruksachatkun et al.*2020 · 89 citations*
46. **[Human vs. Muppet: A Conservative Estimate of Human Performance on the GLUE Benchmark ↗](https://aclanthology.org/P19-1449/) Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yet**Nikita Nangia, Samuel R. Bowman*2019 · 87 citations*
47. **[Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work? ↗](https://arxiv.org/abs/2005.00628) arXiv (Cornell University) · no summary yet**Yada Pruksachatkun et al.*2020 · 83 citations*
48. **[Alignment faking in large language models ↗](https://arxiv.org/abs/2412.14093) arXiv (Cornell University) · no summary yet**Ryan Greenblatt et al.*2024 · 82 citations*
49. **[Question Decomposition Improves the Faithfulness of Model-Generated Reasoning ↗](https://arxiv.org/abs/2307.11768) arXiv (Cornell University) · no summary yet**Ansh Radhakrishnan et al.*2023 · 74 citations*
50. **[Tree-structured composition in neural networks without tree-structured architectures ↗](https://arxiv.org/abs/1506.04834) arXiv:1506.04834 · no summary yet**Samuel R. Bowman, Christopher D. Manning, Christopher Potts*2015 · 73 citations*
51. **[The Dangers of Underclaiming: Reasons for Caution When Reporting How NLP Systems Fail ↗](https://aclanthology.org/2022.acl-long.516/) Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Bowman, Samuel R.*2022 · 72 citations*
52. **[English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too](https://md.research.elamur.ai/free/en/papers/phang-2020-english-intermediate-task-training-improves/) [Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)](https://md.research.elamur.ai/free/en/venues/aacl/)**Jason Phang, Iacer Calixto, Phu Mon Htut, et al.*2020 · 70 citations*
53. **[Can neural networks acquire a structural bias from raw linguistic data? ↗](https://arxiv.org/abs/2007.06761) arXiv (Cornell University) · no summary yet**Alex Warstadt, Samuel R. Bowman*2020 · 70 citations*
54. **[Verb Argument Structure Alternations in Word and Sentence Embeddings ↗](https://aclanthology.org/W19-0129/) Proceedings of the Society for Computation in Linguistics (SCiL) 2019 · no summary yet**Katharina Kann et al.*2019 · 68 citations*
55. **[Let's Think Dot by Dot: Hidden Computation in Transformer Language Models ↗](https://arxiv.org/abs/2404.15758) arXiv:2404.15758 · no summary yet**Jacob Pfau, William Merrill, Samuel R. Bowman*2024 · 67 citations*
56. **[Language Modeling Teaches You More Syntax than Translation Does: Lessons Learned Through Auxiliary Task Analysis ↗](https://arxiv.org/abs/1809.10040) arXiv:1809.10040 · Blackbox NLP Workshop, EMNLP 2018 · no summary yet**Kelly W. Zhang, Samuel R. Bowman*2018 · 65 citations*
57. **[Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set ↗](https://aclanthology.org/D19-1329/) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · no summary yet**Katharina Kann, Kyunghyun Cho, Samuel R. Bowman*2019 · 62 citations*
58. **[Grammar Induction with Neural Language Models: An Unusual Replication ↗](https://aclanthology.org/D18-1544/) Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yet**Phu Mon Htut, Kyunghyun Cho, Samuel R. Bowman*2018 · 61 citations*
59. **[Training a Ranking Function for Open-Domain Question Answering ↗](https://aclanthology.org/N18-4017/) Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop · no summary yet**Phu Mon Htut, Samuel R. Bowman, Kyunghyun Cho*2018 · 54 citations*
60. **[SQuALITY: Building a Long-Document Summarization Dataset the Hard Way ↗](https://aclanthology.org/2022.emnlp-main.75/) Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · no summary yet**Alex Wang et al.*2022 · 51 citations*
61. **[Counterfactually-Augmented SNLI Training Data Does Not Yield Better Generalization Than Unaugmented Data](https://md.research.elamur.ai/free/en/papers/huang-2020-counterfactually-augmented-snli-training-data/) [Workshop on Insights from Negative Results in NLP](https://md.research.elamur.ai/free/en/venues/insights/)**William Huang, Haokun Liu, Samuel R. Bowman*2020 · 51 citations*
62. **[Ruminating Reader: Reasoning with Gated Multi-hop Attention ↗](https://aclanthology.org/W18-2601/) Proceedings of the Workshop on Machine Reading for Question Answering · no summary yet**Yichen Gong, Samuel R. Bowman*2018 · 50 citations*
63. **[Does Putting a Linguist in the Loop Improve NLU Data Collection? ↗](https://aclanthology.org/2021.findings-emnlp.421/) Findings of the Association for Computational Linguistics: EMNLP 2021 · no summary yet**Alicia Parrish et al.*2021 · 49 citations*
64. **[What Ingredients Make for an Effective Crowdsourcing Protocol for Difficult NLU Data Collection Tasks? ↗](https://aclanthology.org/2021.acl-long.98/) Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · no summary yet**Nikita Nangia et al.*2021 · 48 citations*
65. **[Improving Code Generation by Training with Natural Language Feedback ↗](https://arxiv.org/abs/2303.16749) arXiv:2303.16749 · no summary yet**Angelica Chen et al.*2023 · 47 citations*
66. **[Comparing Test Sets with Item Response Theory ↗](https://aclanthology.org/2021.acl-long.92/) Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · no summary yet**Clara Vania et al.*2021 · 47 citations*
67. [**More Constructions, More Genres: Extending Stanford Dependencies**Marie-Catherine de Marneffe, Miriam Connor, Natalia Silveira, et al.*English · 47 citations*](https://md.research.elamur.ai/free/en/papers/marneffe-2013-more-constructions-more-genres-extending/)
68. **[Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models ↗](https://arxiv.org/abs/2406.10162) arXiv (Cornell University) · no summary yet**Carson Denison et al.*2024 · 46 citations*
69. **[Grammatical Analysis of Pretrained Sentence Encoders with Acceptability Judgments. ↗](https://arxiv.org/abs/1901.03438) arXiv (Cornell University) · no summary yet**Alex Warstadt, Samuel R. Bowman*2019 · 45 citations*
70. **[Detecting and Explaining Crisis ↗](https://aclanthology.org/W17-3108/) Proceedings of the Fourth Workshop on Computational Linguistics and Clinical Psychology –- From Linguistic Signal to Clinical Reality · no summary yet**Rohan Kshirsagar, Robert Morris, Samuel R. Bowman*2017 · 41 citations*
71. **[Can recursive neural tensor networks learn logical reasoning? ↗](https://arxiv.org/abs/1312.6192) arXiv (Cornell University) · no summary yet**Samuel R. Bowman*2013 · 41 citations*
72. **[What Do NLP Researchers Believe? Results of the NLP Community Metasurvey ↗](https://aclanthology.org/2023.acl-long.903/) Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Julian Michael et al.*2023 · 40 citations*
73. [**NOPE: A Corpus of Naturally-Occurring Presuppositions in English**Alicia Parrish, Sebastian Schuster, Alex Warstadt, et al.*English · 40 citations*](https://md.research.elamur.ai/free/en/papers/parrish-2021-nope-corpus-naturally-occurring-presuppositions/)
74. **[A Stable and Effective Learning Strategy for Trainable Greedy Decoding ↗](https://aclanthology.org/D18-1035/) Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yet**Yun Chen et al.*2018 · 40 citations*
75. **[(QA)²: Question Answering with Questionable Assumptions ↗](https://aclanthology.org/2023.acl-long.472/) Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Najoung Kim et al.*2023 · 39 citations*
76. **[Fine-Tuned Transformers Show Clusters of Similar Representations Across Layers ↗](https://aclanthology.org/2021.blackboxnlp-1.42/) Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP · no summary yet**Jason Phang, Haokun Liu, Samuel R. Bowman*2021 · 39 citations*
77. **[Speech recognitionwith segmental conditional random fields: A summary of the JHU CLSP 2010 Summer Workshop ↗](https://doi.org/10.1109/icassp.2011.5947490) IEEE International Conference on Acoustics Speech and Signal Processing · no summary yet**Geoffrey Zweig et al.*2011 · 37 citations*
78. **[Looking for ELMo's friends: Sentence-Level Pretraining Beyond Language Modeling. ↗](https://openalex.org/W2907630459) no summary yet**Samuel R. Bowman et al.*2018 · 34 citations*
79. **[Language Models Learn to Mislead Humans via RLHF ↗](https://arxiv.org/abs/2409.12822) arXiv (Cornell University) · no summary yet**Jiaxin Wen et al.*2024 · 33 citations*
80. **[Can Unconditional Language Models Recover Arbitrary Sentences? ↗](https://arxiv.org/abs/1907.04944) arXiv (Cornell University) · no summary yet**Nishant Subramani, Samuel R. Bowman, Kyunghyun Cho*2019 · 29 citations*
81. **[Debate Helps Supervise Unreliable Experts ↗](https://arxiv.org/abs/2311.08702) arXiv (Cornell University) · no summary yet**Julian Michael et al.*2023 · 28 citations*
82. **[Deep Learning for Natural Language Inference ↗](https://aclanthology.org/N19-5002/) Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorials · no summary yet**Samuel R. Bowman, Xiaodan Zhu*2019 · 28 citations*
83. **[ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context Learning ↗](https://aclanthology.org/2023.acl-short.154/) Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) · no summary yet**Jingyuan S. She et al.*2023 · 27 citations*
84. **[New Protocols and Negative Results for Textual Entailment Data Collection](https://md.research.elamur.ai/free/en/papers/bowman-2020-new-protocols-negative-results-textual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Samuel R. Bowman, Jennimaria Palomaki, Livio Baldini Soares, et al.*2020 · 27 citations*
85. **[Automatic Animacy Classification ↗](https://aclanthology.org/N12-2002/) Proceedings of the NAACL HLT 2012 Student Research Workshop · no summary yet**Samuel R. Bowman, Harshit Chopra*2012 · 26 citations*
86. **[Two Failures of Self-Consistency in the Multi-Step Reasoning of LLMs](https://md.research.elamur.ai/free/en/papers/chen-2023-two-failures-self-consistency-multi/) [Transactions on Machine Learning Research](https://md.research.elamur.ai/free/en/venues/transactions-on-machine-learning-research/)**Angelica Chen, Jason Phang, Alicia Parrish, et al.*2023 · 25 citations*
87. **[SocioProbe: What, When, and Where Language Models Learn about Sociodemographics ↗](https://aclanthology.org/2022.emnlp-main.539/) Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · no summary yet**Anne Lauscher et al.*2022 · 24 citations*
88. **[What Makes Reading Comprehension Questions Difficult? ↗](https://aclanthology.org/2022.acl-long.479/) Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Saku Sugawara et al.*2022 · 21 citations*
89. [**BLiMP: The Benchmark of Linguistic Minimal Pairs for English**Alex Warstadt, Alicia Parrish, Haokun Liu, et al.*Mova's core list · 21 citations*](https://md.research.elamur.ai/free/en/papers/warstadt-2020-blimp-benchmark-linguistic-minimal-pairs/)
90. **[Auditing language models for hidden objectives ↗](https://arxiv.org/abs/2503.10965) arXiv (Cornell University) · no summary yet**Marks, Samuel et al.*2025 · 19 citations*
91. **[Adversarially Constructed Evaluation Sets Are More Challenging, but May Not Be Fair ↗](https://aclanthology.org/2022.dadc-1.8/) Proceedings of the First Workshop on Dynamic Adversarial Data Collection · no summary yet**Jason Phang et al.*2022 · 18 citations*
92. **[Precise Task Formalization Matters in Winograd Schema Evaluations ↗](https://aclanthology.org/2020.emnlp-main.664/) Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yet**Haokun Liu et al.*2020 · 18 citations*
93. **[Steering Without Side Effects: Improving Post-Deployment Control of Language Models ↗](https://arxiv.org/abs/2406.15518) arXiv (Cornell University) · no summary yet**Asa Cooper Stickland et al.*2024 · 17 citations*
94. **[Learning Distributed Word Representations for Natural Logic Reasoning ↗](https://arxiv.org/abs/1410.4176) arXiv (Cornell University) · no summary yet**Samuel R. Bowman, Christopher E. Potts, Christopher D. Manning*2014 · 17 citations*
95. **[A Molecular Toolkit to Visualize Native Protein Assemblies in the Context of Human Disease ↗](https://doi.org/10.1038/srep14440) Scientific Reports · no summary yet**Brian L. Gilmore et al.*2015 · 16 citations*
96. **[Learning to Learn Morphological Inflection for Resource-Poor Languages ↗](https://doi.org/10.1609/aaai.v34i05.6316) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Katharina Kann, Samuel R. Bowman, Kyunghyun Cho*2020 · 14 citations*
97. **[Single-Turn Debate Does Not Help Humans Answer Hard Reading-Comprehension Questions ↗](https://aclanthology.org/2022.lnls-1.3/) Proceedings of the First Workshop on Learning with Natural Language Supervision · no summary yet**Alicia Parrish et al.*2022 · 13 citations*
98. **[Sequential Attention: A Context-Aware Alignment Function for Machine Reading ↗](https://aclanthology.org/W17-2610/) Proceedings of the 2nd Workshop on Representation Learning for NLP · no summary yet**Sebastian Brarda, Philip Yeres, Samuel R. Bowman*2017 · 11 citations*
99. **[Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-Thought ↗](https://arxiv.org/abs/2403.05518) arXiv (Cornell University) · no summary yet**James Chua et al.*2024 · 10 citations*
100. **[Asking Crowdworkers to Write Entailment Examples: The Best of Bad Options ↗](https://aclanthology.org/2020.aacl-main.68/) Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing · no summary yet**Clara Vania, Ruijie Chen, Samuel R. Bowman*2020 · 10 citations*

**1** [2](https://md.research.elamur.ai/free/en/authors/samuel-r-bowman/works/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/samuel-r-bowman/works/page/2/)