Papers by Howe Tissue

1 papers
Entropy Scheduling in Reinforcement Learning for Large Language Models (2026.findings-acl)

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Challenge: entropy in reinforcement learning functions analogously to the learning rate in LLMs.
Approach: They propose an entropy scheduling system that optimizes different pre-set goals by controlling and scheduling entropicy at each step of the RL process.
Outcome: The proposed method improves AIME2024 from 50.9 to 54.9 within 40 training steps.

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