219 citations · 330 across the 10 of their papers we have counts for
4 papers · 1 filter
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models
Peter Henderson, Eric Mitchell, Christopher D. Manning +2
A growing ecosystem of large, open-source foundation models has reduced the labeled data and technical expertise necessary to apply machine learning to many new problems. Yet found…
Entropy Regularization for Population Estimation
Ben Chugg, Peter Henderson, Jacob Goldin +1
Entropy regularization is known to improve exploration in sequential decision-making problems. We show that this same mechanism can also lead to nearly unbiased and lower-variance…
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset
Peter Henderson, Mark S. Krass, Lucia Zheng +4
One concern with the rise of large language models lies with their potential for significant harm, particularly from pretraining on biased, obscene, copyrighted, and private inform…
Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection
Peter Henderson, Ben Chugg, Brandon Anderson +5
We introduce a new setting, optimize-and-estimate structured bandits. Here, a policy must select a batch of arms, each characterized by its own context, that would allow it to both…