Daniel E. Ho
Orcid: 0000-0002-2195-5469
According to our database1,
Daniel E. Ho
authored at least 47 papers
between 2019 and 2024.
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Bibliography
2024
Nat. Mac. Intell., 2024
CoRR, 2024
Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risk of Language Models.
CoRR, 2024
Locating and measuring marine aquaculture production from space: a computer vision approach in the French Mediterranean.
CoRR, 2024
CoRR, 2024
FLawN-T5: An Empirical Examination of Effective Instruction-Tuning Data Mixtures for Legal Reasoning.
CoRR, 2024
How well do LLMs cite relevant medical references? An evaluation framework and analyses.
CoRR, 2024
CoRR, 2024
Estimating and Implementing Conventional Fairness Metrics With Probabilistic Protected Features.
Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
2023
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models.
CoRR, 2023
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in U.S. Government.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023
How Redundant are Redundant Encodings? Blindness in the Wild and Racial Disparity when Race is Unobserved.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools.
Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023
The Bureaucratic Challenge to AI Governance: An Empirical Assessment of Implementation at U.S. Federal Agencies.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Author Correction: Advances, challenges and opportunities in creating data for trustworthy AI.
Nat. Mac. Intell., October, 2022
Mapping Industrial Poultry Operations at Scale With Deep Learning and Aerial Imagery.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
Nat. Mach. Intell., 2022
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022
Proceedings of the 2022 Symposium on Computer Science and Law, 2022
Detecting Environmental Violations with Satellite Imagery in Near Real Time: Land Application under the Clean Water Act.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022
2021
A language-matching model to improve equity and efficiency of COVID-19 contact tracing.
Proc. Natl. Acad. Sci. USA, 2021
Reconciling Risk Allocation and Prevalence Estimation in Public Health Using Batched Bandits.
CoRR, 2021
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset.
CoRR, 2021
Enhancing environmental enforcement with near real-time monitoring: Likelihood-based detection of structural expansion of intensive livestock farms.
Int. J. Appl. Earth Obs. Geoinformation, 2021
When does pretraining help?: assessing self-supervised learning for law and the CaseHOLD dataset of 53, 000+ legal holdings.
Proceedings of the ICAIL '21: Eighteenth International Conference for Artificial Intelligence and Law, São Paulo Brazil, June 21, 2021
Proceedings of the ICAIL '21: Eighteenth International Conference for Artificial Intelligence and Law, São Paulo Brazil, June 21, 2021
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021
The Distributive Effects of Risk Prediction in Environmental Compliance: Algorithmic Design, Environmental Justice, and Public Policy.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021
Proceedings of the COMPASS '21: ACM SIGCAS Conference on Computing and Sustainable Societies, Virtual Event, Australia, 28 June 2021, 2021
2020
2019
Is Yelp Actually Cleaning Up the Restaurant Industry? A Re-Analysis on the Relative Usefulness of Consumer Reviews.
Proceedings of the World Wide Web Conference, 2019