Papers14

#pass@k

Meta-RL Induces Exploration in Language Agents

Yulun Jiang, Liangze Jiang et al.Dec 18arXiv

This paper introduces LAMER, a Meta-RL training framework that teaches language agents to explore first and then use what they learned to solve tasks faster.

#Meta-Reinforcement Learning#Language Agents#Exploration vs Exploitation

Can LLMs Guide Their Own Exploration? Gradient-Guided Reinforcement Learning for LLM Reasoning

Intermediate

Zhenwen Liang, Sidi Lu et al.Dec 17arXiv

This paper teaches large language models (LLMs) to explore smarter by listening to their own gradients—the directions they would update—rather than chasing random variety.

#gradient-guided reinforcement learning#GRL#GRPO

1 2