When does pretraining help?: assessing self-supervised learning for law and the CaseHOLD dataset of 53, 000+ legal holdings. - Lucia Zheng; Neel Guha; Brandon R. Anderson; Peter Henderson 002; Daniel E. Ho (ICAIL, 2021)

When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset. - Lucia Zheng; Neel Guha; Brandon R. Anderson; Peter Henderson 002; Daniel E. Ho (CoRR, 2021)

Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. - Peter Henderson 002; Mark S. Krass; Lucia Zheng; Neel Guha; Christopher D. Manning; Dan Jurafsky; Daniel E. Ho (NeurIPS, 2022)

Holistic Evaluation of Language Models. - Percy Liang; Rishi Bommasani; Tony Lee; Dimitris Tsipras; Dilara Soylu; Michihiro Yasunaga; Yian Zhang; Deepak Narayanan; Yuhuai Wu; Ananya Kumar; Benjamin Newman; Binhang Yuan; et al. (Trans. Mach. Learn. Res., 2023)

NLP Systems That Can't Tell Use from Mention Censor Counterspeech, but Teaching the Distinction Helps. - Kristina Gligoric; Myra Cheng; Lucia Zheng; Esin Durmus; Dan Jurafsky (NAACL-HLT, 2024)

FLawN-T5: An Empirical Examination of Effective Instruction-Tuning Data Mixtures for Legal Reasoning. - Joel Niklaus; Lucia Zheng; Arya D. McCarthy; Christopher Hahn; Brian M. Rosen; Peter Henderson 002; Daniel E. Ho; Garrett Honke; Percy Liang; Christopher D. Manning (CoRR, 2024)

A Reasoning-Focused Legal Retrieval Benchmark. - Lucia Zheng; Neel Guha; Javokhir Arifov; Sarah Zhang; Michal Skreta; Christopher D. Manning; Peter Henderson 002; Daniel E. Ho (CSLAW, 2025)

LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domain. - Joel Niklaus; Lucia Zheng; Arya D. McCarthy; Christopher Hahn; Brian M. Rosen; Peter Henderson 002; Daniel E. Ho; Garrett Honke; Percy Liang; Christopher D. Manning (NAACL (Findings), 2025)