Reinforcement Learning Fine-Tuning Enhances Activation Intensity and Diversity in the Internal Circuitry of LLMs

Ähnliche Einträge

• LLM-Explorer: A Plug-in Reinforcement Learning Policy Exploration Enhancement Driven by Large Language Models
  von: Hao, Qianyue, et al.
  Veröffentlicht: (2025)
• Enhancing Reinforcement Learning Fine-Tuning with an Online Refiner
  von: Ma, Hao, et al.
  Veröffentlicht: (2026)
• Multiple Weaks Win Single Strong: Large Language Models Ensemble Weak Reinforcement Learning Agents into a Supreme One
  von: Song, Yiwen, et al.
  Veröffentlicht: (2025)
• Internalizing Curriculum Judgment for LLM Reinforcement Fine-Tuning
  von: Zheng, Han, et al.
  Veröffentlicht: (2026)
• Supervised Fine-Tuning as Inverse Reinforcement Learning
  von: Sun, Hao
  Veröffentlicht: (2024)