Publications
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Unpublished manuscript, 2023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Unpublished manuscript, 2023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Unpublished manuscript, 2023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, Alicia 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
Can self-supervised neural networks learn 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 at most 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