Papers

For papers after August 2023, see Google Scholar.

Roger Grosse, Juhan Bae, Cem Anil, Nelson Elhage, Alex Tamkin, Amirhossein Tajdini, Benoit Steiner, Dustin Li, Esin Durmus, Ethan Perez, Evan Hubinger, Kamilė Lukošiūtė, Karina Nguyen, Nicholas Joseph, Sam McCandlish, Jared Kaplan, and Samuel R. Bowman Studying Large Language Model Generalization with Influence Functions Unpublished manuscript, 2023

Ansh Radhakrishnan, Karina Nguyen, Anna Chen, Carol Chen, Carson Denison, Danny Hernandez, Esin Durmus, Evan Hubinger, Jackson Kernion, Kamilė Lukošiūtė, Newton Cheng, Nicholas Joseph, Nicholas Schiefer, Oliver Rausch, Sam McCandlish, Sheer El Showk, Tamera Lanham, Tim Maxwell, Venkatesa Chandrasekaran, Zac Hatfield-Dodds, Jared Kaplan, Jan Brauner, Samuel R. Bowman, and Ethan Perez Question Decomposition Improves the Faithfulness of Model-Generated Reasoning Unpublished manuscript, 2023

Tamera Lanham, Anna Chen, Ansh Radhakrishnan, Benoit Steiner, Carson Denison, Danny Hernandez, Dustin Li, Esin Durmus, Evan Hubinger, Jackson Kernion, Kamilė Lukošiūtė, Karina Nguyen, Newton Cheng, Nicholas Joseph, Nicholas Schiefer, Oliver Rausch, Robin Larson, Sam McCandlish, Sandipan Kundu, Saurav Kadavath, Shannon Yang, Thomas Henighan, Timothy Maxwell, Timothy Telleen-Lawton, Tristan Hume, Zac Hatfield-Dodds, Jared Kaplan, Jan Brauner, Samuel R. Bowman, and Ethan Perez Measuring Faithfulness in Chain-of-Thought Reasoning Unpublished manuscript, 2023

Ian R. McKenzie, Alexander Lyzhov, Michael Pieler, Alicia Parrish, Aaron Mueller, Ameya Prabhu, Euan McLean, Aaron Kirtland, Alexis Ross, Alisa Liu, Andrew Gritsevskiy, Daniel Wurgaft, Derik Kauffman, Gabriel Recchia, Jiacheng Liu, Joe Cavanagh, Max Weiss, Sicong Huang, The Floating Droid, Tom Tseng, Tomasz Korbak, Xudong Shen, Yuhui Zhang, Zhengping Zhou, Najoung Kim, Samuel R. Bowman, and Ethan Perez Inverse Scaling: When Bigger Isn't Better (data) Transactions on Machine Learning Research, 2023

Jingyuan S. She, Christopher Potts, Samuel R. Bowman, and Atticus Geiger ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context Learning (data) Proceedings of ACL, 2023

Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, and Samuel R. Bowman What Do NLP Researchers Believe? Results of the NLP Community Metasurvey (results viewer) Proceedings of ACL, 2023

Or Honovich, Uri Shaham, Samuel R. Bowman, and Omer Levy Instruction Induction: From Few Examples to Natural Language Task Descriptions (code and data) Proceedings of ACL, 2023

Angelica Chen, Jason Phang, Alicia Parrish, Vishakh Padmakumar, Chen Zhao, Samuel R. Bowman, Kyunghyun Cho Two Failures of Self-Consistency in the Multi-Step Reasoning of LLMs Unpublished manuscript, 2023

Miles Turpin, Julian Michael, Ethan Perez, and Samuel R. Bowman Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting (code and data) Unpublished manuscript, 2023

Samuel R. Bowman Eight Things to Know about Large Language Models Unpublished manuscript, 2023

Large collaboration, 445 authors Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (code and data) TMLR, 2023

Angelica Chen, Jérémy Scheurer, Tomasz Korbak, Jon Ander Campos, Jun Shern Chan, Samuel R. Bowman, Kyunghyun Cho, and Ethan Perez Improving Code Generation by Training with Natural Language Feedback (code and data) Unpublished manuscript, 2023

Tomasz Korbak, Kejian Shi, Angelica Chen, Rasika Bhalerao, Christopher L Buckley, Jason Phang, Samuel R Bowman, and Ethan Perez Pretraining Language Models with Human Preferences (code and data) Proceedings of ICML, 2023

Deep Ganguli, Amanda Askell, Nicholas Schiefer, Thomas I. Liao, Kamilė Lukošiūtė, Anna Chen, Anna Goldie, Azalia Mirhoseini, Catherine Olsson, Danny Hernandez, Dawn Drain, Dustin Li, Eli Tran-Johnson, Ethan Perez, Jackson Kernion, Jamie Kerr, Jared Mueller, Joshua Landau, Kamal Ndousse, Karina Nguyen, Liane Lovitt, Michael Sellitto, Nelson Elhage, Noemi Mercado, Nova DasSarma, Oliver Rausch, Robert Lasenby, Robin Larson, Sam Ringer, Sandipan Kundu, Saurav Kadavath, Scott Johnston, Shauna Kravec, Sheer El Showk, Tamera Lanham, Timothy Telleen-Lawton, Tom Henighan, Tristan Hume, Yuntao Bai, Zac Hatfield-Dodds, Ben Mann, Dario Amodei, Nicholas Joseph, Sam McCandlish, Tom Brown, Christopher Olah, Jack Clark, Samuel R. Bowman, and Jared Kaplan The Capacity for Moral Self-Correction in Large Language Models Unpublished manuscript, 2023

Najoung Kim, Phu Mon Htut, Samuel R. Bowman, and Jackson Petty (QA)²: Question Answering with Questionable Assumptions (data) Proceedings of ACL, 2023

Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, Karina Nguyen, Edwin Chen, Scott Heiner, Craig Pettit, Catherine Olsson, Sandipan Kundu, Saurav Kadavath, Andy Jones, Anna Chen, Ben Mann, Brian Israel, Bryan Seethor, Cameron McKinnon, Christopher Olah, Da Yan, Daniela Amodei, Dario Amodei, Dawn Drain, Dustin Li, Eli Tran-Johnson, Guro Khundadze, Jackson Kernion, James Landis, Jamie Kerr, Jared Mueller, Jeeyoon Hyun, Joshua Landau, Kamal Ndousse, Landon Goldberg, Liane Lovitt, Martin Lucas, Michael Sellitto, Miranda Zhang, Neerav Kingsland, Nelson Elhage, Nicholas Joseph, Noemí Mercado, Nova DasSarma, Oliver Rausch, Robin Larson, Sam McCandlish, Scott Johnston, Shauna Kravec, Sheer El Showk, Tamera Lanham, Timothy Telleen-Lawton, Tom Brown, Tom Henighan, Tristan Hume, Yuntao Bai, Zac Hatfield-Dodds, Jack Clark, Samuel R. Bowman, Amanda Askell, Roger Grosse, Danny Hernandez, Deep Ganguli, Evan Hubinger, Nicholas Schiefer, and Jared Kaplan Discovering Language Model Behaviors with Model-Written Evaluations (data, interactive viewer) Unpublished manuscript, 2022

Alex Warstadt and Samuel R. Bowman What Artificial Neural Networks Can Tell Us about Human Language Acquisition In Shalom Lappin and Jean-Philippe Bernardy (Eds.), Algebraic Structures in Natural Language, 2022

Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, Carol Chen, Catherine Olsson, Christopher Olah, Danny Hernandez, Dawn Drain, Deep Ganguli, Dustin Li, Eli Tran-Johnson, Ethan Perez, Jamie Kerr, Jared Mueller, Jeffrey Ladish, Joshua Landau, Kamal Ndousse, Kamile Lukosuite, Liane Lovitt, Michael Sellitto, Nelson Elhage, Nicholas Schiefer, Noemi Mercado, Nova DasSarma, Robert Lasenby, Robin Larson, Sam Ringer, Scott Johnston, Shauna Kravec, Sheer El Showk, Stanislav Fort, Tamera Lanham, Timothy Telleen-Lawton, Tom Conerly, Tom Henighan, Tristan Hume, Samuel R. Bowman, Zac Hatfield-Dodds, Ben Mann, Dario Amodei, Nicholas Joseph, Sam McCandlish, Tom Brown, and Jared Kaplan Constitutional AI: Harmlessness from AI Feedback Unpublished manuscript, 2022

Samuel R. Bowman, Jeeyoon Hyun, Ethan Perez, Edwin Chen, Craig Pettit, Scott Heiner, Kamile Lukosiute, Amanda Askell, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, Christopher Olah, Daniela Amodei, Dario Amodei, Dawn Drain, Dustin Li, Eli Tran-Johnson, Jackson Kernion, Jamie Kerr, Jared Mueller, Jeffrey Ladish, Joshua Landau, Kamal Ndousse, Liane Lovitt, Nelson Elhage, Nicholas Schiefer, Nicholas Joseph, Noemí Mercado, Nova DasSarma, Robin Larson, Sam McCandlish, Sandipan Kundu, Scott Johnston, Shauna Kravec, Sheer El Showk, Stanislav Fort, Timothy Telleen-Lawton, Tom Brown, Tom Henighan, Tristan Hume, Yuntao Bai, Zac Hatfield-Dodds, Ben Mann, and Jared Kaplan Measuring Progress on Scalable Oversight for Large Language Models (data) Unpublished manuscript, 2022

Alex Wang, Richard Yuanzhe Pang, Angelica Chen, Jason Phang, and Samuel R. Bowman SQuALITY: Building a Long-Document Summarization Dataset the Hard Way (data and code) Proceedings of EMNLP, 2022

Anne Lauscher, Federico Bianchi, Samuel R. Bowman, Dirk Hovy SocioProbe: What, When, and Where Language Models Learn about Sociodemographics (code) Proceedings of EMNLP, 2022

{Alicia Parrish, Harsh Trivedi}, Nikita Nangia, Vishakh Padmakumar, Jason Phang, Amanpreet Singh Saimbhi, and Samuel R. Bowman Two-Turn Debate Doesn't Help Humans Answer Hard Reading Comprehension Questions Proceedings of the NeurIPS ML Safety Workshop, 2022

The Anthropic Technical Staff Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned Unpublished manuscript, 2022

The Anthropic Technical Staff Language Models (Mostly) Know What They Know Unpublished manuscript, 2022

{Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi}, Nikita Nangia, Jason Phang, Angelica Chen, Vishakh Padmakumar, Johnny Ma, Jana Thompson, He He, and Samuel R. Bowman QuALITY: Question Answering with Long Input Texts, Yes! (data and code) Proceedings of NAACL, 2022

Samuel R. Bowman The Dangers of Underclaiming: Reasons for Caution When Reporting How NLP Systems Fail Proceedings of ACL, 2022

Alicia Parrish, Angelica Chen, Nikita Nangia, Vishakh Padmakumar, Jason Phang, Jana Thompson, Phu Mon Htut, and Samuel R. Bowman BBQ: A Hand-Built Bias Benchmark for Question Answering (data and code) Findings of ACL, 2022

Saku Sugawara, Nikita Nangia, Alex Warstadt, and Samuel R. Bowman What Makes Reading Comprehension Questions Difficult? (preprint) Proceedings of ACL, 2022

{Alicia Parrish, Harsh Trivedi, Ethan Perez}, Angelica Chen, Nikita Nangia, Jason Phang, and Samuel R. Bowman Single-Turn Debate Does Not Help Humans Answer Hard Reading-Comprehension Questions Proceedings of The First Workshop on Learning with Natural Language Supervision, 2022

Jason Phang, Angelica Chen, William Huang, and Samuel R. Bowman Adversarially Constructed Evaluation Sets Are More Challenging, but May Not Be Fair Unpublished manuscript, 2021

Derek Chen, Zhou Yu, and Samuel R. Bowman Clean or Annotate: How to Spend a Limited Data Collection Budget Proceedings of the Third Workshop Deep Learning for Low-Resource NLP, 2022

{Alicia Parrish, Sebastian Schuster, Alex Warstadt}, Omar S. Agha, Soo-Hwan Lee, Zhuoye Zhaoo, Samuel R. Bowman and Tal Linzen NOPE: A Corpus of Naturally-Occurring Presuppositions in English (corpus page) Proceedings of CoNLL, 2021

Alicia Parrish, William Huang, Omar Agha, Soo-Hwan Lee, Nikita Nangia, Alex Warstadt, Karmanya Aggarwal, Emily Allaway, Tal Linzen, and Samuel R. Bowman Does Putting a Linguist in the Loop Improve NLU Data Collection? (code and data) Findings of EMNLP, 2021

Jason Phang, Haokun Liu, and Samuel R. Bowman Fine-Tuned Transformers Show Clusters of Similar Representations Across Layers Proceedings of BlackboxNLP, 2021

{Nikita Nangia, Saku Sugawara}, Harsh Trivedi, Alex Warstadt, Clara Vania, and Samuel R. Bowman What Ingredients Make for an Effective Crowdsourcing Protocol for Difficult NLU Data Collection Tasks? (code and data) Proceedings of ACL, 2021

{Clara Vania, Phu Mon Htut, William Huang}, Dhara Mungra, Richard Yuanzhe Pang, Jason Phang, Haokun Liu, Kyunghyun Cho, and Samuel R. Bowman Comparing Test Sets with Item Response Theory (code and data) Proceedings of ACL, 2021

{Yian Zhang, Alex Warstadt}, Haau-Sing Li, and Samuel R. Bowman When Do You Need Billions of Words of Pretraining Data? (code) Proceedings of ACL, 2021

Samuel R. Bowman and George E. Dahl What Will it Take to Fix Benchmarking in Natural Language Understanding? (slides for the 45-minute version of the talk) Proceedings of NAACL, 2021

Clara Vania, Ruijie Chen, and Samuel R. Bowman Asking Crowdworkers to Write Entailment Examples: The Best of Bad Options (code and data) Proceedings of AACL, 2020

{Jason Phang, Iacer Calixto}, Phu Mon Htut, Yada Pruksachatkun, Haokun Liu, Clara Vania, Katharina Kann, and Samuel R. Bowman English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too (code) Proceedings of AACL, 2020

Alex Warstadt, Yian Zhang, Haau-Sing Li, Haokun Liu, and Samuel R. Bowman Learning Which Features Matter: RoBERTa Acquires a Preference for Linguistic Generalizations (Eventually) (code and data) Proceedings of EMNLP, 2020

{Haokun Liu, William Huang}, Dhara A. Mungra, and Samuel R. Bowman Precise Task Formalization Matters in Winograd Schema Evaluations (code) Proceedings of EMNLP (short paper), 2020

Samuel R. Bowman, Jennimaria Palomaki, Livio Baldini Soares, and Emily Pitler New Protocols and Negative Results for Textual Entailment Data Collection (code and data) Proceedings of EMNLP, 2020

{Nikita Nangia, Clara Vania, Rasika Bhalerao}, and Samuel R. Bowman CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models (code and data) Proceedings of EMNLP, 2020

William Huang, Haokun Liu, and Samuel R. Bowman Counterfactually-Augmented SNLI Training Data Does Not Yield Better Generalization Than Unaugmented Data (code and data) Proceedings of the Workshop on Insights from Negative Results in NLP, 2020

Alex Warstadt and Samuel R. Bowman Do self-supervised neural networks acquire a bias towards structural linguistic generalizations? (code and data) Proceedings of CogSci, 2020

Anhad Mohananey, Katharina Kann, and Samuel R. Bowman Self-Training for Unsupervised Parsing with PRPN (code) Proceedings of IWPT, 2020

{Yada Pruksachatkun, Jason Phang, Haokun Liu, Phu Mon Htut}, Xiaoyi Zhang, Richard Yuanzhe Pang, Clara Vania, Katharina Kann, and Samuel R. Bowman Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work? Proceedings of ACL, 2020

{Yada Pruksachatkun, Phil Yeres}, Haokun Liu, Jason Phang, Phu Mon Htut, Alex Wang, Ian Tenney, and Samuel R. Bowman jiant: A Software Toolkit for Research on General-Purpose Text Understanding Models (project site) Proceedings of ACL (demonstration track), 2020

Alex Warstadt, Alicia Parrish, Haokun Liu, Anhad Mohananey, Wei Peng, Sheng-Fu Wang, and Samuel R. Bowman BLiMP: A Benchmark of Linguistic Minimal Pairs for English (project site) Transactions of the ACL (TACL), 2020

Katharina Kann, Samuel R. Bowman, and Kyunghyun Cho Learning to Learn Morphological Inflection for Resource-Poor Languages Proceedings of AAAI, 2020

Phu Mon Htut, Jason Phang, Shikha Bordia, and Samuel R. Bowman Do Attention Heads in BERT Track Syntactic Dependencies? Unpublished manuscript, 2019

Phu Mon Htut, Kyunghyun Cho, and Samuel R. Bowman Inducing Constituency Trees through Neural Machine Translation Unpublished manuscript, 2019

Katharina Kann, Anhad Mohananey, Samuel R. Bowman and Kyunghyun Cho Neural Unsupervised Parsing Beyond English Proceedings of The Workshop on Deep Learning for Low-Resource NLP (DeepLo), 2019

{Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh}, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems (project site, baseline code) Proceedings of NeurIPS, 2019

Nishant Subramani, Samuel R. Bowman, and Kyunghyun Cho Can Unconditional Language Models Recover Arbitrary Sentences? Proceedings of NeurIPS, 2019

{Alex Warstadt, Yu Cao, Ioana Grosu, Wei Peng, Hagen Blix, Yining Nie, Anna Alsop, Shikha Bordia, Haokun Liu, Alicia Parrish, Sheng-Fu Wang, Jason Phang, Anhad Mohananey, Phu Mon Htut, Paloma Jeretic} and Samuel R. Bowman Investigating BERT’s Knowledge of Language: Five Analysis Methods with NPIs (code and data) Proceedings of EMNLP, 2019

Katharina Kann, Kyunghyun Cho, and Samuel R. Bowman Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set Proceedings of EMNLP, 2019

Alex Warstadt, Amanpreet Singh, and Samuel R. Bowman Neural Network Acceptability Judgments (corpus page) Transactions of the ACL (TACL), 2019

Alex Wang, Jan Hula, Patrick Xia, Raghavendra Pappagari, R. Thomas Mccoy, Roma Patel, Najoung Kim, Ian Tenney, Yinghui Huang, Katherin Yu, Shuning Jin, Berlin Chen, Benjamin Van Durme, Edouard Grave, Ellie Pavlick, and Samuel R. Bowman Can You Tell Me How to Get Past Sesame Street: Sentence-Level Pretraining Beyond Language Modeling (code) Proceedings of ACL, 2019

Nikita Nangia and Samuel R. Bowman Human vs. Muppet: A Conservative Estimate of Human Performance on the GLUE Benchmark Proceedings of ACL, 2019

Najoung Kim, Roma Patel, Adam Poliak, Patrick Xia, Alex Wang, Tom McCoy, Ian Tenney, Alexis Ross, Tal Linzen, Benjamin Van Durme, Samuel R. Bowman and Ellie Pavlick Probing What Different NLP Tasks Teach Machines about Function Word Comprehension (code) Proceedings of *SEM, 2019 Best Paper Award

{Jason Phang, Thibault Févry} and Samuel R. Bowman Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks Unpublished manuscript, 2019

Chandler May, Alex Wang, Shikha Bordia, Samuel R. Bowman and Rachel Rudinger On Measuring Social Biases in Sentence Encoders Proceedings of NAACL, 2019

Shikha Bordia and Samuel R. Bowman Identifying and Reducing Gender Bias in Word-Level Language Models Proceedings of the NAACL Student Research Workshop, 2019

Alex Warstadt and Samuel R. Bowman Grammatical Analysis of Pretrained Sentence Encoders with Acceptability Judgments (data) Unpublished manuscript, 2019

Samuel R. Bowman, Ellie Pavlick, Edouard Grave, Benjamin Van Durme, Alex Wang, Jan Hula, Patrick Xia, Raghavendra Pappagari, R. Thomas McCoy, Roma Patel, Najoung Kim, Ian Tenney, Yinghui Huang, Katherin Yu, Shuning Jin, and Berlin Chen Looking for ELMo's Friends: Sentence-Level Pretraining Beyond Language Modeling (code) Unpublished manuscript superseded by Can You Tell Me How to Get Past Sesame Street, above, 2019

Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding (project site) Proceedings of ICLR, 2019

Ian Tenney, Patrick Xia, Berlin Chen, Alex Wang, Adam Poliak, R. Thomas McCoy, Najoung Kim, Benjamin Van Durme, Samuel R. Bowman, Dipanjan Das, and Ellie Pavlick What do you learn from context? Probing for sentence structure in contextualized word representations (code) Proceedings of ICLR, 2019

Kelly W. Zhang and Samuel R. Bowman Language Modeling Teaches You More Syntax than Translation Does: Lessons Learned Through Auxiliary Task Analysis Unpublished manuscript, 2018

{Katharina Kann, Alex Warstadt, Adina Williams} and Samuel R. Bowman Verb Argument Structure Alternations in Word and Sentence Embeddings (corpus page) Proceedings of SCiL, 2018

Yun Chen, Victor O.K. Li, Kyunghyun Cho and Samuel R. Bowman A Stable and Effective Learning Strategy for Trainable Greedy Decoding Proceedings of EMNLP, 2018

Alexis Conneau, Ruty Rinott, Guillaume Lample, Adina Williams, Samuel R. Bowman, Holger Schwenk and Veselin Stoyanov XNLI: Cross-lingual Sentence Understanding through Inference (corpus page) Proceedings of EMNLP, 2018

Phu Mon Htut, Kyunghyun Cho, and Samuel R. Bowman Grammar Induction with Neural Language Models: An Unusual Replication (code) Proceedings of EMNLP (short paper), 2018

WooJin Chung, Sheng-Fu Wang, and Samuel R. Bowman The Lifted Matrix-Space Model for Semantic Composition Proceedings of CoNLL, 2018

Nikita Nangia and Samuel R. Bowman ListOps: A Diagnostic Dataset for Latent Tree Learning (code and data) Proceedings of the NAACL Student Research Workshop, 2018

Phu Mon Htut, Samuel R. Bowman, and Kyunghyun Cho Training a Ranking Function for Open-Domain Question Answering Proceedings of the NAACL Student Research Workshop, 2018

Adina Williams, Nikita Nangia, and Samuel R. Bowman A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference (corpus page) Proceedings of NAACL, 2018

Adina Williams, Andrew Drozdov, and Samuel R. Bowman Do latent tree learning models identify meaningful structure in sentences? (code) Transactions of the ACL (TACL), 2018

Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel R. Bowman, and Noah A. Smith Annotation Artifacts in Natural Language Inference Data (data on the MultiNLI corpus page) Proceedings of NAACL (short paper), 2018

Yichen Gong and Samuel R. Bowman Ruminating Reader: Reasoning with Gated Multi-Hop Attention Proceedings of the Workshop on Machine Reading for Question Answering, 2018

Nikita Nangia, Adina Williams, Angeliki Lazaridou, and Samuel R. Bowman The RepEval 2017 Shared Task: Multi-Genre Natural Language Inference with Sentence Representations Proceedings of RepEval 2017: The Second Workshop on Evaluating Vector Space Representations for NLP, 2017

Rohan Kshirsagar, Robert Morris, and Samuel R. Bowman Detecting and Explaining Crisis Proceedings of The 2017 Computational Linguistics and Clinical Psychology Workshop, 2017

Sebastian Brarda, Philip Yeres, and Samuel R. Bowman Sequential Attention Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Yacine Jernite, Samuel R. Bowman, and David Sontag Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning Unpublished manuscript, 2017

Samuel R. Bowman Modeling natural language semantics in learned representations Stanford University Dissertation, 2016

{Samuel R. Bowman, Luke Vilnis}, Oriol Vinyals, Andrew M. Dai, Rafal Jozefowicz, and Samy Bengio Generating Sentences from a Continuous Space Proceedings of CoNLL, 2016

{Samuel R. Bowman, Jon Gauthier}, Abhinav Rastogi, Raghav Gupta, Christopher D. Manning, and Christopher Potts A Fast Unified Model for Parsing and Sentence Understanding (code) Proceedings of ACL, 2016

Samuel R. Bowman, Christopher D. Manning, and Christopher Potts Tree-structured composition in neural networks without tree-structured architectures Proceedings of the NIPS Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches, 2015

Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning A large annotated corpus for learning natural language inference (corpus page) Proceedings of EMNLP, 2015 Best New Data Set or Resource Award

Samuel R. Bowman, Christopher Potts, and Christopher D. Manning Recursive Neural Networks Can Learn Logical Semantics (code and data, poster) Proceedings of The 3rd Workshop on Continuous Vector Space Models and their Compositionality, 2015

Samuel R. Bowman, Christopher Potts, and Christopher D. Manning Learning Distributed Word Representations for Natural Logic Reasoning Proceedings of the AAAI Spring Symposium on Knowledge Representation and Reasoning, 2015

Natalia Silveira, Timothy Dozat, Marie-Catherine de Marneffe, Samuel R. Bowman, Miriam Connor, John Bauer, and Christopher D. Manning A Gold Standard Dependency Corpus for English Proceedings of LREC, 2014

Samuel R. Bowman Can recursive neural tensor networks learn logical reasoning? (code and data) Unpublished manuscript, 2014

Samuel R. Bowman and Benjamin Lokshin Idiosyncratic transparent vowels in Kazakh Proceedings of AMP, 2013 A typo in item (39) in the published version is corrected here.

Marie-Catherine de Marneffe, Miriam Connor, Natalia Silveira, Samuel R. Bowman, Timothy Dozat and Christopher D. Manning More constructions, more genres: Extending Stanford Dependencies Proceedings of DepLing, 2013

Samuel R. Bowman Two arguments for vowel harmony by trigger competition Proceedings of CLS, 2013

Samuel R. Bowman and Harshit Chopra Automatic animacy classification (poster) Proceedings of The NAACL Student Research Workshop, 2012

Samuel R. Bowman Vowel varmony, opacity, and finite-state OT Technical report TR-2011-03, Department of Computer Science, The University of Chicago.

Geoffrey Zweig, Les Atlas, Kris Demuynck, Fei Sha, Patrick Nguyen, Dirk van Compernolle, Damianos Karakos, Pascal Clark, Meihong Wang, Gregory Sell, Samuel Thomas, Samuel R. Bowman and Justine Kao Speech recognition with segmental conditional random fields: A summary of the JHU CLSP 2010 Summer Workshop Proceedings of ICASSP, 2011

Samuel R. Bowman and Karen Livescu Modeling pronunciation variation with context-dependent articulatory feature decision trees Proceedings of Interspeech, 2010

An aside: My Erdős number is 4, by way of Karen Livescu, Kamalika Chaudhuri, and Fan Chung, by way of Chris Manning, Val Spitkovsky, and Daniel Kleitman, by way of Anne Lauscher, Philipp Zumstein, and Noga Alon, or by way of Victor O.K. Li, Kuang Xu, and Joel H. Spencer.

Talk slides, etc.

Samuel R. Bowman Adversarial Scalable Oversight for Truthfulness: Work in Progress (video) The Alignment Workshop, 2023

Samuel R. Bowman A few technical points to keep in mind when discussing technologies like ChatGPT Slides for the panel AI FUTURES with Critical AI, 2023

Samuel R. Bowman Why Adversarially-Collected Test Sets Don't Work as Benchmarks Slides for an Invited Talk at The First Workshop on Dynamic Adversarial Data Collection (DADC), 2022

Alane Suhr, Clara Vania, Nikita Nangia, Maarten Sap, Mark Yatskar, Samuel R. Bowman, and Yoav Artzi Crowdsourcing Beyond Annotation: Case Studies in Benchmark Data Collection EMNLP Tutorial, 2021

Samuel R. Bowman How do we fix natural language understanding evaluation? Invited talk slides for a CMU ML Department virtual invited talk, 2020

Samuel R. Bowman Evaluating Recent Progress Toward General-Purpose Language Understanding Models Invited talk slides for a Google Research virtual invited talk, 2020

Samuel R. Bowman Evaluating Recent Progress Toward General-Purpose Language Understanding Models (video) Invited talk slides for the Allen Institute for AI and the University of Washington, 2019

Samuel R. Bowman Task-Independent Language Understanding Invited talk slides for Cornell and IBM Research, 2019

Samuel R. Bowman Task-Independent Sentence Understanding Models *SEM/SemEval joint invited talk slides, 2019

Samuel R. Bowman and Xiaodan Zhu Deep Learning for Natural Language Inference NAACL tutorial, 2019

Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning A large annotated corpus of entailments and contradictions Talk Slides from California Universities Semantics and Pragmatics, 2015

Samuel R. Bowman Computational Linguistics Guest lecture for an introductory linguistics class with Asya Pereltsvaig, 2015

Samuel R. Bowman Neural networks for natural language understanding Guest lecture for Chris Potts and Bill MacCartney's computational natural language understanding class, 2015

Samuel R. Bowman vector-entailment: A MATLAB toolkit for tree-structured recursive neural networks 2015

Samuel R. Bowman Transparent vowels in ABC: open issues ABC↔Conference invited talk handout, 2014

Samuel R. Bowman Seto vowel harmony and neutral vowels Presentation at LSA, 2013

Richard Futrell and Samuel R. Bowman Measuring amok Course paper, 2012