--- title: "Samuel R. Bowman — papers and cards" description: "Samuel R. Bowman: 3 paper cards in the Research library (2013–2021), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/samuel-r-bowman/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/samuel-r-bowman/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Samuel R. Bowman # Samuel R. Bowman 3 paper cards in the Research library · 2013–2021 Samuel R. Bowman wrote 3 of the papers Mova reads, in 2013–2021; often with [Alex Warstadt](https://md.research.elamur.ai/free/en/authors/alex-warstadt/), [Alicia Parrish](https://md.research.elamur.ai/free/en/authors/alicia-parrish/), Anhad Mohananey. [OpenAlex](https://openalex.org/A5112713734) · [**h-index 48**](https://openalex.org/authors/A5112713734) · [21012 citations](https://openalex.org/authors/A5112713734) · [139 works](https://openalex.org/works?filter=author.id:A5112713734) — openalex-snapshot, 2026-10-14 The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Samuel+R.+Bowman) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Samuel+R.+Bowman) · [dblp](https://dblp.org/search?q=Samuel+R.+Bowman) · [ACL Anthology](https://aclanthology.org/search/?q=Samuel+R.+Bowman) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Samuel+R.+Bowman) ## Papers 1. **[NOPE: A Corpus of Naturally-Occurring Presuppositions in English](https://md.research.elamur.ai/free/en/papers/parrish-2021-nope-corpus-naturally-occurring-presuppositions/)** *(2021)* NOPE collects about 1,280 corpus passages, each with a presupposition trigger of one of ten types: change of state, aspectual verbs (begin, stop), clause-embedding verbs (know, realize, say), clefts, comparatives, embedded questions, implicatives (manage to, fail to), numeric determiners (both), re- verbs, and… 2. **[BLiMP: The Benchmark of Linguistic Minimal Pairs for English](https://md.research.elamur.ai/free/en/papers/warstadt-2020-blimp-benchmark-linguistic-minimal-pairs/)** *(2020)* BLiMP is a challenge set for measuring which parts of English grammar language models have learned. It contains 67 paradigms of 1,000 sentence pairs each; within a pair the two sentences differ minimally and only one is acceptable. The pairs are generated automatically from templates designed by linguists and cover… 3. **[More Constructions, More Genres: Extending Stanford Dependencies](https://md.research.elamur.ai/free/en/papers/bank-2013-marneffe-more-constructions-more-genres-extending/)** *(2013)* The Stanford scheme was built on newswire and gives little analysis to constructions that are rare there but common in web text: tough adjectives, free relatives, comparatives, small clauses, questions, imperatives, fragments and lists. ## Co-authors (16) - [Alex Warstadt](https://md.research.elamur.ai/free/en/authors/alex-warstadt/) ×2 - [Alicia Parrish](https://md.research.elamur.ai/free/en/authors/alicia-parrish/) ×2 - Anhad Mohananey - [Christopher D. Manning](https://md.research.elamur.ai/free/en/authors/christopher-d-manning/) - Haokun Liu - [Marie-Catherine de Marneffe](https://md.research.elamur.ai/free/en/authors/marie-catherine-de-marneffe/) - Miriam Connor - [Natalia Silveira](https://md.research.elamur.ai/free/en/authors/natalia-silveira/) - Omar Agha - [Sebastian Schuster](https://md.research.elamur.ai/free/en/authors/sebastian-schuster/) - Sheng-Fu Wang - [Soo-Hwan Lee](https://md.research.elamur.ai/free/en/authors/soo-hwan-lee/) - [Tal Linzen](https://md.research.elamur.ai/free/en/authors/tal-linzen/) - [Timothy Dozat](https://md.research.elamur.ai/free/en/authors/timothy-dozat/) - Wei Peng - Zhuoye Zhao ## More papers in the library (16) Pages of the Research library: our summary, the ideas, references and who cites each. - [GPQA: A Graduate-Level Google-Proof Q&A Benchmark](https://md.research.elamur.ai/free/en/papers/rein-2023-gpqa-graduate-level-google-proof/) — David Rein, Betty Li Hou, Asa Cooper Stickland, et al. · 2023 - [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/) — Miles Turpin, Julian Michael, Ethan Perez, et al. · 2023 - [Pretraining Language Models with Human Preferences](https://md.research.elamur.ai/free/en/papers/korbak-2023-pretraining-language-models-human-preferences/) — Tomasz Korbak, Kejian Shi, Angelica Chen, et al. · 2023 - [Towards Understanding Sycophancy in Language Models](https://md.research.elamur.ai/free/en/papers/sharma-2023-towards-understanding-sycophancy-language-models/) — Mrinank Sharma, Meg Tong, Tomasz Korbak, et al. · 2023 - [BBQ: A hand-built bias benchmark for question answering](https://md.research.elamur.ai/free/en/papers/parrish-2022-bbq-hand-built-bias-benchmark/) — Alicia Parrish, Angelica Chen, Nikita Nangia, et al. · 2022 - [QuALITY: Question Answering with Long Input Texts, Yes!](https://md.research.elamur.ai/free/en/papers/pang-2022-quality-question-answering-long-input/) — Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, et al. · 2022 - [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/) — Nikita Nangia, Clara Vania, Rasika Bhalerao, et al. · 2020 - [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/) — Yada Pruksachatkun, Jason Phang, Haokun Liu, et al. · 2020 - [Identifying and Reducing Gender Bias in Word-Level Language Models](https://md.research.elamur.ai/free/en/papers/bordia-2019-identifying-reducing-gender-bias-word/) — Shikha Bordia, Samuel R. Bowman · 2019 - [On Measuring Social Biases in Sentence Encoders](https://md.research.elamur.ai/free/en/papers/may-2019-measuring-social-biases-sentence-encoders/) — Chandler May, Alex Wang, Shikha Bordia, et al. · 2019 - [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/) — Najoung Kim, Roma Patel, Adam Poliak, et al. · 2019 - [SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems](https://md.research.elamur.ai/free/en/papers/wang-2019-superglue-stickier-benchmark-general-purpose/) — Alex Wang, Yada Pruksachatkun, Nikita Nangia, et al. · 2019 - [What do you learn from context? Probing for sentence structure in contextualized word representations](https://md.research.elamur.ai/free/en/papers/tenney-2019-learn-context-probing-sentence-structure/) — Ian Tenney, Patrick Xia, Berlin Chen, et al. · 2019 - [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/) — Alex Wang, Amanpreet Singh, Julian Michael, et al. · 2018 - [Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks](https://md.research.elamur.ai/free/en/papers/phang-2018-sentence-encoders-stilts-supplementary-training/) — Jason Phang, Thibault Févry, Samuel R. Bowman · 2018 - [Generating Sentences from a Continuous Space](https://md.research.elamur.ai/free/en/papers/bowman-2016-generating-sentences-continuous-space/) — Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al. · 2016