AINeutralarXiv โ CS AI ยท 14h ago6/10
๐ง
Tail-Aware Information-Theoretic Generalization for RLHF and SGLD
Researchers develop a new information-theoretic framework that handles heavy-tailed data distributions, addressing limitations in classical generalization bounds used in machine learning. The work applies specifically to reinforcement learning from human feedback (RLHF) and stochastic gradient optimization, where traditional KL-divergence tools fail due to non-existent moment generating functions.