LLMs trained with simple rewards often latch onto just a few ways of solving problems and stop exploring, which hurts their ability to find other correct answers.

#DSDR#dual-scale diversity#RLVR

Collaborative Multi-Agent Test-Time Reinforcement Learning for Reasoning

Intermediate

Zhiyuan Hu, Yunhai Hu et al.Jan 14arXiv

This paper introduces MATTRL, a way for multiple AI agents to learn from their own conversations at test time using short, reusable text notes instead of retraining their weights.

#multi-agent systems#test-time reinforcement learning#experience retrieval

From Imitation to Discrimination: Toward A Generalized Curriculum Advantage Mechanism Enhancing Cross-Domain Reasoning Tasks

Intermediate

Changpeng Yang, Jinyang Wu et al.Dec 2arXiv

This paper teaches AI models to reason better by first copying only good examples and later learning from mistakes too.

#Curriculum Advantage Policy Optimization#advantage-based RL#imitation learning