NaturalProofs: Mathematical Theorem Proving in Natural Language. - Sean Welleck; Jiacheng Liu 010; Ronan Le Bras 001; Hanna Hajishirzi; Yejin Choi 001; Kyunghyun Cho (NeurIPS Datasets and Benchmarks, 2021)

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)

Rainier: Reinforced Knowledge Introspector for Commonsense Question Answering. - Jiacheng Liu 010; Skyler Hallinan; Ximing Lu; Pengfei He; Sean Welleck; Hannaneh Hajishirzi; Yejin Choi 001 (EMNLP, 2022)

NaturalProver: Grounded Mathematical Proof Generation with Language Models. - Sean Welleck; Jiacheng Liu 010; Ximing Lu; Hannaneh Hajishirzi; Yejin Choi 001 (NeurIPS, 2022)

Crystal: Introspective Reasoners Reinforced with Self-Feedback. - Jiacheng Liu 010; Ramakanth Pasunuru; Hannaneh Hajishirzi; Yejin Choi 001; Asli Celikyilmaz (EMNLP, 2023)

Vera: A General-Purpose Plausibility Estimation Model for Commonsense Statements. - Jiacheng Liu 010; Wenya Wang 001; Dianzhuo Wang; Noah A. Smith; Yejin Choi 001; Hannaneh Hajishirzi (EMNLP, 2023)

Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs. - Albert Qiaochu Jiang; Sean Welleck; Jin Peng Zhou; Timothée Lacroix; Jiacheng Liu 010; Wenda Li; Mateja Jamnik; Guillaume Lample; Yuhuai Wu (ICLR, 2023)

Making PPO even better: Value-Guided Monte-Carlo Tree Search decoding. - Jiacheng Liu 010; Andrew Cohen; Ramakanth Pasunuru; Yejin Choi 001; Hannaneh Hajishirzi; Asli Celikyilmaz (CoRR, 2023)

MathVista: Evaluating Math Reasoning in Visual Contexts with GPT-4V, Bard, and Other Large Multimodal Models. - Pan Lu; Hritik Bansal; Tony Xia; Jiacheng Liu 010; Chunyuan Li; Hannaneh Hajishirzi; Hao Cheng 002; Kai-Wei Chang; Michel Galley; Jianfeng Gao 001 (CoRR, 2023)

Inverse Scaling: When Bigger Isn't Better. - 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; et al. (Trans. Mach. Learn. Res., 2023)

Are Machines Better at Complex Reasoning? Unveiling Human-Machine Inference Gaps in Entailment Verification. - Soumya Sanyal 001; Tianyi Xiao; Jiacheng Liu 010; Wenya Wang 001; Xiang Ren 001 (ACL (Findings), 2024)

MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts. - Pan Lu; Hritik Bansal; Tony Xia; Jiacheng Liu 010; Chunyuan Li; Hannaneh Hajishirzi; Hao Cheng 002; Kai-Wei Chang; Michel Galley; Jianfeng Gao 001 (ICLR, 2024)

Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback. - Hamish Ivison; Yizhong Wang; Jiacheng Liu 010; Zeqiu Wu; Valentina Pyatkin; Nathan Lambert 001; Noah A. Smith; Yejin Choi 001; Hanna Hajishirzi (NeurIPS, 2024)

Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens. - Jiacheng Liu 010; Sewon Min; Luke Zettlemoyer; Yejin Choi 001; Hannaneh Hajishirzi (CoRR, 2024)

Establishing Task Scaling Laws via Compute-Efficient Model Ladders. - Akshita Bhagia; Jiacheng Liu 010; Alexander Wettig; David Heineman; Oyvind Tafjord; Ananya Harsh Jha; Luca Soldaini; Noah A. Smith; Dirk Groeneveld; Pang Wei Koh; Jesse Dodge; Hannaneh Hajishirzi (CoRR, 2024)

AI as Humanity's Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text. - Ximing Lu; Melanie Sclar; Skyler Hallinan; Niloofar Mireshghallah; Jiacheng Liu 010; Seungju Han 002; Allyson Ettinger; Liwei Jiang; Khyathi Raghavi Chandu; Nouha Dziri; Yejin Choi 001 (ICLR, 2025)

2 OLMo 2 Furious. - Team OLMo; Pete Walsh; Luca Soldaini; Dirk Groeneveld; Kyle Lo; Shane Arora; Akshita Bhagia; Yuling Gu; Shengyi Huang; Matt Jordan; Nathan Lambert 001; Dustin Schwenk; et al. (CoRR, 2025)

OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens. - Jiacheng Liu 010; Taylor Blanton; Yanai Elazar; Sewon Min; Yen-Sung Chen; Arnavi Chheda-Kothary; Huy Tran; Byron Bischoff; Eric Marsh; Michael Schmitz 002; Cassidy Trier; Aaron Sarnat; et al. (CoRR, 2025)

DataDecide: How to Predict Best Pretraining Data with Small Experiments. - Ian Magnusson; Nguyen Tai; Ben Bogin; David Heineman; Jena D. Hwang; Luca Soldaini; Akshita Bhagia; Jiacheng Liu 010; Dirk Groeneveld; Oyvind Tafjord; Noah A. Smith; Pang Wei Koh; et al. (CoRR, 2025)

ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data. - Tong Chen; Faeze Brahman; Jiacheng Liu 010; Niloofar Mireshghallah; Weijia Shi; Pang Wei Koh; Luke Zettlemoyer; Hannaneh Hajishirzi (CoRR, 2025)

Large Language Models Are More Persuasive Than Incentivized Human Persuaders. - Philipp Schoenegger; Francesco Salvi; Jiacheng Liu 010; Xiaoli Nan; Ramit Debnath; Barbara Fasolo; Evelina Leivada; Gabriel Recchia; Fritz Günther; Ali Zarifhonarvar; Joe Kwon; Zahoor Ul Islam; et al. (CoRR, 2025)

Infini-gram mini: Exact n-gram Search at the Internet Scale with FM-Index. - Hao Xu; Jiacheng Liu 010; Yejin Choi 001; Noah A. Smith; Hannaneh Hajishirzi (CoRR, 2025)