AIBullisharXiv – CS AI · 3h ago7/10
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AEM: Adaptive Entropy Modulation for Multi-Turn Agentic Reinforcement Learning
Researchers present AEM (Adaptive Entropy Modulation), a new credit assignment method for reinforcement learning that improves how language model agents learn from sparse rewards without requiring dense supervision. The technique adaptively modulates entropy during training to balance exploration and exploitation, achieving a 1.4% improvement on the challenging SWE-bench-Verified benchmark across models ranging from 1.5B to 32B parameters.