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cs.LG2026
Bayesian Learning to Select Fair Classifiers
Saatvik Kher, Hyungrok Do, Judy Zhong +1
Evaluations of classifiers (AI or human or agents) often assume a batch setting in which every agent produces labels on every example in a test set, which can be expensive or impra…
cs.LG2026
PEARL: Training Socratic Tutors with Pedagogically Aligned Reinforcement Learning
Qikai Chang, Zhenrong Zhang, Linbo Chen +4
Large Language Models (LLMs) show strong potential as educational tutors. Existing approaches typically train them to solve problems and provide correct answers, but this problem-s…