Speculative Design and Heterogeneity in Indigenous Nation Building. - Yoko Akama; Seth Keen; Peter West (Conference on Designing Interactive Systems, 2016)

The Quantified Patient in the Doctor's Office: Challenges & Opportunities. - Peter West; Richard Giordano; Max Van Kleek; Nigel Shadbolt (CHI, 2016)

Designing digital and creative scaffolds to strengthen Indigenous nations: being Wiradjuri by practising sovereignty. - Yoko Akama; Debra Evans; Seth Keen; Faye McMillan; Mark McMillan; Peter West (Digit. Creativity, 2017)

Common Barriers to the Use of Patient-Generated Data Across Clinical Settings. - Peter West; Max Van Kleek; Richard Giordano; Mark J. Weal; Nigel Shadbolt (CHI, 2018)

"A Game Without Competition Is Hardly a Game": The Impact of Competitions on Player Activity in a Human Computation Game". - Neal Reeves; Peter West; Elena Simperl (HCOMP, 2018)

BottleSum: Unsupervised and Self-supervised Sentence Summarization using the Information Bottleneck Principle. - Peter West; Ari Holtzman; Jan Buys; Yejin Choi 001 (EMNLP/IJCNLP (1), 2019)

Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning. - Lianhui Qin; Vered Shwartz; Peter West; Chandra Bhagavatula; Jena D. Hwang; Ronan Le Bras 001; Antoine Bosselut; Yejin Choi 001 (EMNLP (1), 2020)

Unsupervised Commonsense Question Answering with Self-Talk. - Vered Shwartz; Peter West; Ronan Le Bras 001; Chandra Bhagavatula; Yejin Choi 001 (EMNLP (1), 2020)

PLink: Discovering and Exploiting Locality for Accelerated Distributed Training on the public Cloud. - Liang Luo; Peter West; Arvind Krishnamurthy; Luis Ceze; Jacob Nelson 001 (MLSys, 2020)

Reflective Decoding: Unsupervised Paraphrasing and Abductive Reasoning. - Peter West; Ximing Lu; Ari Holtzman; Chandra Bhagavatula; Jena D. Hwang; Yejin Choi 001 (CoRR, 2020)

Srift: Swift and Thrift Cloud-Based Distributed Training. - Liang Luo; Peter West; Arvind Krishnamurthy; Luis Ceze (CoRR, 2020)

Reflective Decoding: Beyond Unidirectional Generation with Off-the-Shelf Language Models. - Peter West; Ximing Lu; Ari Holtzman; Chandra Bhagavatula; Jena D. Hwang; Yejin Choi 001 (ACL/IJCNLP (1), 2021)

Surface Form Competition: Why the Highest Probability Answer Isn't Always Right. - Ari Holtzman; Peter West; Vered Shwartz; Yejin Choi 001; Luke Zettlemoyer (EMNLP (1), 2021)

NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints. - Ximing Lu; Peter West; Rowan Zellers; Ronan Le Bras 001; Chandra Bhagavatula; Yejin Choi 001 (NAACL-HLT, 2021)

Symbolic Brittleness in Sequence Models: On Systematic Generalization in Symbolic Mathematics. - Sean Welleck; Peter West; Jize Cao; Yejin Choi 001 (AAAI, 2022)

Generated Knowledge Prompting for Commonsense Reasoning. - Jiacheng Liu 010; Alisa Liu; Ximing Lu; Sean Welleck; Peter West; Ronan Le Bras 001; Yejin Choi 001; Hannaneh Hajishirzi (ACL (1), 2022)

Probing Factually Grounded Content Transfer with Factual Ablation. - Peter West; Chris Quirk; Michel Galley; Yejin Choi 001 (ACL (Findings), 2022)

Referee: Reference-Free Sentence Summarization with Sharper Controllability through Symbolic Knowledge Distillation. - Melanie Sclar; Peter West; Sachin Kumar 009; Yulia Tsvetkov; Yejin Choi 001 (EMNLP, 2022)

Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference. - Galen Weld; Peter West; Maria Glenski; David Arbour; Ryan A. Rossi; Tim Althoff (ICWSM, 2022)

SRIFTY: Swift and Thrifty Distributed Neural Network Training on the Cloud. - Liang Luo; Peter West; Pratyush Patel; Arvind Krishnamurthy; Luis Ceze (MLSys, 2022)

NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics. - Ximing Lu; Sean Welleck; Peter West; Liwei Jiang; Jungo Kasai; Daniel Khashabi; Ronan Le Bras 001; Lianhui Qin; Youngjae Yu; Rowan Zellers; Noah A. Smith; Yejin Choi 001 (NAACL-HLT, 2022)

Symbolic Knowledge Distillation: from General Language Models to Commonsense Models. - Peter West; Chandra Bhagavatula; Jack Hessel; Jena D. Hwang; Liwei Jiang; Ronan Le Bras 001; Ximing Lu; Sean Welleck; Yejin Choi 001 (NAACL-HLT, 2022)

QUARK: Controllable Text Generation with Reinforced Unlearning. - Ximing Lu; Sean Welleck; Jack Hessel; Liwei Jiang; Lianhui Qin; Peter West; Prithviraj Ammanabrolu; Yejin Choi 001 (NeurIPS, 2022)

I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation. - Chandra Bhagavatula; Jena D. Hwang; Doug Downey; Ronan Le Bras 001; Ximing Lu; Keisuke Sakaguchi; Swabha Swayamdipta; Peter West; Yejin Choi 001 (CoRR, 2022)

I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation. - Chandra Bhagavatula; Jena D. Hwang; Doug Downey; Ronan Le Bras 001; Ximing Lu; Lianhui Qin; Keisuke Sakaguchi; Swabha Swayamdipta; Peter West; Yejin Choi 001 (ACL (1), 2023)

Minding Language Models' (Lack of) Theory of Mind: A Plug-and-Play Multi-Character Belief Tracker. - Melanie Sclar; Sachin Kumar 009; Peter West; Alane Suhr; Yejin Choi 001; Yulia Tsvetkov (ACL (1), 2023)

SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization. - Hyunwoo Kim 002; Jack Hessel; Liwei Jiang; Peter West; Ximing Lu; Youngjae Yu; Pei Zhou; Ronan Le Bras 001; Malihe Alikhani; Gunhee Kim; Maarten Sap; Yejin Choi 001 (EMNLP, 2023)

We're Afraid Language Models Aren't Modeling Ambiguity. - Alisa Liu; Zhaofeng Wu; Julian Michael; Alane Suhr; Peter West; Alexander Koller; Swabha Swayamdipta; Noah A. Smith; Yejin Choi 001 (EMNLP, 2023)

Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. - Ximing Lu; Faeze Brahman; Peter West; Jaehun Jung; Khyathi Raghavi Chandu; Abhilasha Ravichander; Prithviraj Ammanabrolu; Liwei Jiang; Sahana Ramnath; Nouha Dziri; Jillian Fisher; Bill Y. Lin; et al. (EMNLP, 2023)

NovaCOMET: Open Commonsense Foundation Models with Symbolic Knowledge Distillation. - Peter West; Ronan Le Bras 001; Taylor Sorensen; Bill Yuchen Lin; Liwei Jiang; Ximing Lu; Khyathi Raghavi Chandu; Jack Hessel; Ashutosh Baheti; Chandra Bhagavatula; Yejin Choi 001 (EMNLP (Findings), 2023)

Generating Sequences by Learning to Self-Correct. - Sean Welleck; Ximing Lu; Peter West; Faeze Brahman; Tianxiao Shen; Daniel Khashabi; Yejin Choi 001 (ICLR, 2023)

Faith and Fate: Limits of Transformers on Compositionality. - Nouha Dziri; Ximing Lu; Melanie Sclar; Xiang Lorraine Li; Liwei Jiang; Bill Yuchen Lin; Sean Welleck; Peter West; Chandra Bhagavatula; Ronan Le Bras 001; Jena D. Hwang; Soumya Sanyal 001; et al. (NeurIPS, 2023)

Localized Symbolic Knowledge Distillation for Visual Commonsense Models. - Jae Sung Park; Jack Hessel; Khyathi Raghavi Chandu; Paul Pu Liang; Ximing Lu; Peter West; Youngjae Yu; Qiuyuan Huang; Jianfeng Gao 001; Ali Farhadi; Yejin Choi 001 (NeurIPS, 2023)

Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing. - Jaehun Jung; Peter West; Liwei Jiang; Faeze Brahman; Ximing Lu; Jillian Fisher; Taylor Sorensen; Yejin Choi 001 (CoRR, 2023)

Generative Models as a Complex Systems Science: How can we make sense of large language model behavior? - Ari Holtzman; Peter West; Luke Zettlemoyer (CoRR, 2023)

Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties. - Taylor Sorensen; Liwei Jiang; Jena D. Hwang; Sydney Levine; Valentina Pyatkin; Peter West; Nouha Dziri; Ximing Lu; Kavel Rao; Chandra Bhagavatula; Maarten Sap; John Tasioulas; et al. (AAAI, 2024)

The Generative AI Paradox: "What It Can Create, It May Not Understand". - Peter West; Ximing Lu; Nouha Dziri; Faeze Brahman; Linjie Li; Jena D. Hwang; Liwei Jiang; Jillian Fisher; Abhilasha Ravichander; Khyathi Raghavi Chandu; Benjamin Newman; Pang Wei Koh; et al. (ICLR, 2024)

Impossible Distillation for Paraphrasing and Summarization: How to Make High-quality Lemonade out of Small, Low-quality Model. - Jaehun Jung; Peter West; Liwei Jiang; Faeze Brahman; Ximing Lu; Jillian Fisher; Taylor Sorensen; Yejin Choi 001 (NAACL-HLT, 2024)

Information-Theoretic Distillation for Reference-less Summarization. - Jaehun Jung; Ximing Lu; Liwei Jiang; Faeze Brahman; Peter West; Pang Wei Koh; Yejin Choi 001 (CoRR, 2024)

Predicting vs. Acting: A Trade-off Between World Modeling & Agent Modeling. - Margaret Li; Weijia Shi; Artidoro Pagnoni; Peter West; Ari Holtzman (CoRR, 2024)

Benchmarks as Microscopes: A Call for Model Metrology. - Michael Saxon; Ari Holtzman; Peter West; William Yang Wang; Naomi Saphra (CoRR, 2024)

Hidden Capabilities and Counterintuitive Limits in Large Language Models - Peter West (2024)

BottleHumor: Self-Informed Humor Explanation using the Information Bottleneck Principle. - Eunjeong Hwang; Peter West; Vered Shwartz (ACL (Findings), 2025)

Base Models Beat Aligned Models at Randomness and Creativity. - Peter West; Christopher Potts (CoRR, 2025)

AbsenceBench: Language Models Can't Tell What's Missing. - Harvey Yiyun Fu; Aryan Shrivastava; Jared Moore; Peter West; Chenhao Tan; Ari Holtzman (CoRR, 2025)