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Open problems and fundamental limitations of reinforcement learning from human feedback
S Casper, X Davies, C Shi, TK Gilbert… - ar** to commit crimes or producing racist text. One approach to fine …
[HTML][HTML] Fairness for machine learning software in education: A systematic map** study
The integration of machine learning (ML) systems into various sectors, notably education,
has great potential to transform business workflows and decision-making processes …
has great potential to transform business workflows and decision-making processes …
Personalized language modeling from personalized human feedback
Personalized large language models (LLMs) are designed to tailor responses to individual
user preferences. While Reinforcement Learning from Human Feedback (RLHF) is a …
user preferences. While Reinforcement Learning from Human Feedback (RLHF) is a …
Proportional aggregation of preferences for sequential decision making
We study the problem of fair sequential decision making given voter preferences. In each
round, a decision rule must choose a decision from a set of alternatives where each voter …
round, a decision rule must choose a decision from a set of alternatives where each voter …