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On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models

Intermediate

Shumin Wang, Yuexiang Xie et al.Feb 3arXiv

The paper builds a simple, math-light rule to predict whether training makes a language model more open-minded (higher entropy) or more sure of itself (lower entropy).

#reinforcement fine-tuning#entropy dynamics#GRPO

RE-TRAC: REcursive TRAjectory Compression for Deep Search Agents

Intermediate

Jialiang Zhu, Gongrui Zhang et al.Feb 2arXiv

Re-TRAC is a new way for AI search agents to learn from each try, write a clean summary of what happened, and then use that summary to do better on the next try.

#Re-TRAC#trajectory compression#deep research agents

Bottom-up Policy Optimization: Your Language Model Policy Secretly Contains Internal Policies

Beginner

Yuqiao Tan, Minzheng Wang et al.Dec 22arXiv

Large language models (LLMs) don’t act as a single brain; inside, each layer and module quietly makes its own mini-decisions called internal policies.

#Bottom-up Policy Optimization#internal layer policy#internal modular policy

Papers3

On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models

RE-TRAC: REcursive TRAjectory Compression for Deep Search Agents

Bottom-up Policy Optimization: Your Language Model Policy Secretly Contains Internal Policies