Look Inward to Explore Outward: Learning Temperature Policy from LLM Internal States via Hierarchical RL | ScienceToStartup | ScienceToStartup

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References (52)

[1]

Temperature as a Meta-Policy: Adaptive Temperature in LLM Reinforcement Learning

2026Haoran Dang, Cuiling Lan et al.

[2]

Evaluating Parameter Efficient Methods for RLVR

2025Qingyu Yin, Yulun Wu et al.

[3]

The End of Manual Decoding: Towards Truly End-to-End Language Models

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"Develop an AI framework that dynamically adjusts language model exploration using learned temperature strategies for better task-specific performance."

Reinforcement Learning•Score: 5•View PDF ↗

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Look Inward to Explore Outward: Learning Temperature Policy from LLM Internal States via Hierarchical RL

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References (52)

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"Develop an AI framework that dynamically adjusts language model exploration using learned temperature strategies for better task-specific performance."

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Look Inward to Explore Outward: Learning Temperature Policy from LLM Internal States via Hierarchical RL

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References (52)

Founder's Pitch

"Develop an AI framework that dynamically adjusts language model exploration using learned temperature strategies for better task-specific performance."

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