Is Yelp Actually Cleaning Up the Restaurant Industry? A Re-Analysis on the Relative Usefulness of Consumer Reviews. - Kristen M. Altenburger; Daniel E. Ho (WWW, 2019)

Affirmative Algorithms: The Legal Grounds for Fairness as Awareness. - Daniel E. Ho; Alice Xiang (CoRR, 2020)

Temporal Cluster Matching for Change Detection of Structures from Satellite Imagery. - Caleb Robinson; Anthony Ortiz; Juan M. Lavista Ferres; Brandon R. Anderson; Daniel E. Ho (COMPASS, 2021)

The Distributive Effects of Risk Prediction in Environmental Compliance: Algorithmic Design, Environmental Justice, and Public Policy. - Elinor Benami; Reid Whitaker; Vincent La; Hongjin Lin; Brandon R. Anderson; Daniel E. Ho (FAccT, 2021)

Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy. - Amanda Coston; Neel Guha; Derek Ouyang; Lisa Lu; Alexandra Chouldechova; Daniel E. Ho (FAccT, 2021)

Context-aware legal citation recommendation using deep learning. - Zihan Huang; Charles Low; Mengqiu Teng; Hongyi Zhang; Daniel E. Ho; Mark S. Krass; Matthias Grabmair (ICAIL, 2021)

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)

Enhancing environmental enforcement with near real-time monitoring: Likelihood-based detection of structural expansion of intensive livestock farms. - Ben Chugg; Brandon R. Anderson; Seiji Eicher; Sandy Lee; Daniel E. Ho (Int. J. Appl. Earth Obs. Geoinformation, 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)

On the Opportunities and Risks of Foundation Models. - Rishi Bommasani; Drew A. Hudson; Ehsan Adeli 001; Russ B. Altman; Simran Arora; Sydney von Arx; Michael S. Bernstein; Jeannette Bohg; Antoine Bosselut; Emma Brunskill; Erik Brynjolfsson; Shyamal Buch; et al. (CoRR, 2021)

Reconciling Risk Allocation and Prevalence Estimation in Public Health Using Batched Bandits. - Ben Chugg; Daniel E. Ho (CoRR, 2021)

Beyond Ads: Sequential Decision-Making Algorithms in Public Policy. - Peter Henderson 002; Ben Chugg; Brandon R. Anderson; Daniel E. Ho (CoRR, 2021)

A language-matching model to improve equity and efficiency of COVID-19 contact tracing. - Lisa Lu; Benjamin Anderson; Raymond Ha; Alexis D'Agostino; Sarah L. Rudman; Derek Ouyang; Daniel E. Ho (Proc. Natl. Acad. Sci. USA, 2021)

Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance. - Inioluwa Deborah Raji; Peggy Xu; Colleen Honigsberg; Daniel E. Ho (AIES, 2022)

Detecting Environmental Violations with Satellite Imagery in Near Real Time: Land Application under the Clean Water Act. - Ben Chugg; Nicolas Rothbacher; Alex Feng; Xiaoqi Long; Daniel E. Ho (CIKM, 2022)

Beyond Ads: Sequential Decision-Making Algorithms in Law and Public Policy. - Peter Henderson 002; Ben Chugg; Brandon R. Anderson; Daniel E. Ho (CSLAW, 2022)

Algorithmic Fairness and Vertical Equity: Income Fairness with IRS Tax Audit Models. - Emily Black; Hadi Elzayn; Alexandra Chouldechova; Jacob Goldin; Daniel E. Ho (FAccT, 2022)

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)

LegalBench: Prototyping a Collaborative Benchmark for Legal Reasoning. - Neel Guha; Daniel E. Ho; Julian Nyarko; Christopher Ré (CoRR, 2022)

Advances, challenges and opportunities in creating data for trustworthy AI. - Weixin Liang; Girmaw Abebe Tadesse; Daniel E. Ho; Li Fei-Fei 001; Matei Zaharia; Ce Zhang 001; James Zou 001 (Nat. Mach. Intell., 2022)

Mapping Industrial Poultry Operations at Scale With Deep Learning and Aerial Imagery. - Caleb Robinson; Ben Chugg; Brandon R. Anderson; Juan M. Lavista Ferres; Daniel E. Ho (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

Author Correction: Advances, challenges and opportunities in creating data for trustworthy AI. - Weixin Liang; Girmaw Abebe Tadesse; Daniel E. Ho; Li Fei-Fei 001; Matei Zaharia; Ce Zhang 001; James Zou 001 (Nat. Mac. Intell., 2022)

Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection. - Peter Henderson 002; Ben Chugg; Brandon R. Anderson; Kristen M. Altenburger; Alex Turk; John Guyton; Jacob Goldin; Daniel E. Ho (AAAI, 2023)

Entropy Regularization for Population Estimation. - Ben Chugg; Peter Henderson 002; Jacob Goldin; Daniel E. Ho (AAAI, 2023)

The Bureaucratic Challenge to AI Governance: An Empirical Assessment of Implementation at U.S. Federal Agencies. - Christie Lawrence; Isaac Cui; Daniel E. Ho (AIES, 2023)

Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools. - Emily Black; Rakshit Naidu; Rayid Ghani; Kit T. Rodolfa; Daniel E. Ho; Hoda Heidari (EAAMO, 2023)

How Redundant are Redundant Encodings? Blindness in the Wild and Racial Disparity when Race is Unobserved. - Lingwei Cheng; Isabel O. Gallegos; Derek Ouyang; Jacob Goldin; Daniel E. Ho (FAccT, 2023)

The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in U.S. Government. - Jennifer King; Daniel E. Ho; Arushi Gupta; Victor Wu; Helen Webley-Brown (FAccT, 2023)

LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models. - Neel Guha; Julian Nyarko; Daniel E. Ho; Christopher Ré; Adam Chilton; K. Aditya; Alex Chohlas-Wood; Austin Peters; Brandon Waldon; Daniel N. Rockmore; Diego Zambrano; Dmitry Talisman; et al. (NeurIPS, 2023)

Estimating Racial Disparities When Race is Not Observed. - Cory McCartan; Jacob Goldin; Daniel E. Ho; Kosuke Imai (CoRR, 2023)

Potential for allocative harm in an environmental justice data tool. - Benjamin Q. Huynh; Elizabeth T. Chin; Allison Koenecke; Derek Ouyang; Daniel E. Ho; Mathew V. Kiang; David H. Rehkopf (CoRR, 2023)

SCALE: Scaling up the Complexity for Advanced Language Model Evaluation. - Vishvaksenan Rasiah; Ronja Stern; Veton Matoshi; Matthias Stürmer; Ilias Chalkidis; Daniel E. Ho; Joel Niklaus (CoRR, 2023)

LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models. - Neel Guha; Julian Nyarko; Daniel E. Ho; Christopher Ré; Adam Chilton; Aditya Narayana; Alex Chohlas-Wood; Austin Peters; Brandon Waldon; Daniel N. Rockmore; Diego Zambrano; Dmitry Talisman; et al. (CoRR, 2023)

MultiLegalPile: A 689GB Multilingual Legal Corpus. - Joel Niklaus; Veton Matoshi; Matthias Stürmer; Ilias Chalkidis; Daniel E. Ho (ACL (1), 2024)

Regulating AI Adaptation: An Analysis of AI Medical Device Updates. - Kevin Wu; Eric Wu; Kit T. Rodolfa; Daniel E. Ho; James Zou 001 (CHIL, 2024)

Statistical Uncertainty in Word Embeddings: GloVe-V. - Andrea Vallebueno; Cassandra Handan-Nader; Christopher D. Manning; Daniel E. Ho (EMNLP, 2024)

Position: On the Societal Impact of Open Foundation Models. - Sayash Kapoor; Rishi Bommasani; Kevin Klyman; Shayne Longpre; Ashwin Ramaswami; Peter Cihon; Aspen K. Hopkins; Kevin Bankston; Stella Biderman; Miranda Bogen; Rumman Chowdhury; Alex Engler; et al. (ICML, 2024)

Estimating and Implementing Conventional Fairness Metrics With Probabilistic Protected Features. - Hadi Elzayn; Emily Black; Patrick Vossler; Nathanael Jo; Jacob Goldin; Daniel E. Ho (SaTML, 2024)

Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models. - Matthew Dahl; Varun Magesh; Mirac Suzgun; Daniel E. Ho (CoRR, 2024)

How well do LLMs cite relevant medical references? An evaluation framework and analyses. - Kevin Wu; Eric Wu; Ally Cassasola; Angela Zhang; Kevin Wei; Teresa Nguyen; Sith Riantawan; Patricia Shi Riantawan; Daniel E. Ho; James Zou 001 (CoRR, 2024)

On the Societal Impact of Open Foundation Models. - Sayash Kapoor; Rishi Bommasani; Kevin Klyman; Shayne Longpre; Ashwin Ramaswami; Peter Cihon; Aspen K. Hopkins; Kevin Bankston; Stella Biderman; Miranda Bogen; Rumman Chowdhury; Alex Engler; et al. (CoRR, 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)

Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools. - Varun Magesh; Faiz Surani; Matthew Dahl; Mirac Suzgun; Christopher D. Manning; Daniel E. Ho (CoRR, 2024)

Locating and measuring marine aquaculture production from space: a computer vision approach in the French Mediterranean. - Sebastian Quaade; Andrea Vallebueno; Olivia D. N. Alcabes; Kit T. Rodolfa; Daniel E. Ho (CoRR, 2024)

Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risk of Language Models. - Andy K. Zhang; Neil Perry; Riya Dulepet; Eliot Jones; Justin W. Lin; Joey Ji; Celeste Menders; Gashon Hussein; Samantha Liu; Donovan Jasper; Pura Peetathawatchai; Ari Glenn; et al. (CoRR, 2024)

Belief in the Machine: Investigating Epistemological Blind Spots of Language Models. - Mirac Suzgun; Tayfun Gur; Federico Bianchi 001; Daniel E. Ho; Thomas Icard; Dan Jurafsky; James Zou 001 (CoRR, 2024)

Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice. - A. Feder Cooper; Christopher A. Choquette-Choo; Miranda Bogen; Matthew Jagielski; Katja Filippova; Ken Ziyu Liu; Alexandra Chouldechova; Jamie Hayes; Yangsibo Huang; Niloofar Mireshghallah; Ilia Shumailov; Eleni Triantafillou; et al. (CoRR, 2024)

Mitigating allocative tradeoffs and harms in an environmental justice data tool. - Benjamin Q. Huynh; Elizabeth T. Chin; Allison Koenecke; Derek Ouyang; Daniel E. Ho; Mathew V. Kiang; David H. Rehkopf (Nat. Mac. Intell., 2024)

Fairness through Difference Awareness: Measuring Desired Group Discrimination in LLMs. - Angelina Wang; Michelle Phan; Daniel E. Ho; Sanmi Koyejo (ACL (1), 2025)

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)

Bias Delayed is Bias Denied? Assessing the Effect of Reporting Delays on Disparity Assessments. - Jennah Gosciak; Aparna Balagopalan; Derek Ouyang; Allison Koenecke; Marzyeh Ghassemi; Daniel E. Ho (FAccT, 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)

Artificial Intelligence in Environmental Protection: The Importance of Organizational Context from a Field Study in Wisconsin. - Nicolas Rothbacher; Kit T. Rodolfa; Mihir Bhaskar; Erin Maneri; Christine Tsang; Daniel E. Ho (CoRR, 2025)

AI for Scaling Legal Reform: Mapping and Redacting Racial Covenants in Santa Clara County. - Faiz Surani; Mirac Suzgun; Vyoma Raman; Christopher D. Manning; Peter Henderson 002; Daniel E. Ho (CoRR, 2025)

Extracting memorized pieces of (copyrighted) books from open-weight language models. - A. Feder Cooper; Aaron Gokaslan; Amy Cyphert; Christopher De Sa; Mark A. Lemley; Daniel E. Ho; Percy Liang (CoRR, 2025)

BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systems. - Andy K. Zhang; Joey Ji; Celeste Menders; Riya Dulepet; Thomas Qin; Ron Y. Wang; Junrong Wu; Kyleen Liao; Jiliang Li; Jinghan Hu; Sara Hong; Nardos Demilew; et al. (CoRR, 2025)

The California Report on Frontier AI Policy. - Rishi Bommasani; Scott R. Singer; Ruth E. Appel; Sarah Cen; A. Feder Cooper; Elena Cryst; Lindsey A. Gailmard; Ian Klaus; Meredith M. Lee; Inioluwa Deborah Raji; Anka Reuel; Drew Spence; et al. (CoRR, 2025)

Bridging Prediction and Intervention Problems in Social Systems. - Lydia T. Liu; Inioluwa Deborah Raji; Angela Zhou; Luke Guerdan; Jessica Hullman; Daniel Malinsky; Bryan Wilder; Simone Zhang; Hammaad Adam; Amanda Coston; Benjamin Laufer; Ezinne Nwankwo; et al. (CoRR, 2025)

Advancing Science- and Evidence-based AI Policy. - Rishi Bommasani; Sanjeev Arora; Jennifer T. Chayes; Yejin Choi 001; Mariano-Florentino Cuellar; Li Fei-Fei 001; Daniel E. Ho; Dan Jurafsky; Sanmi Koyejo; Hima Lakkaraju; Arvind Narayanan; Alondra Nelson; et al. (CoRR, 2025)