Paper Notes

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文件夹: Papers/Agent/RL

此文件夹下有20条笔记。

2026年5月
Imperfect World Models are Exploitable
2026年5月
RubricEM: Meta-RL with Rubric-guided Policy Decomposition beyond Verifiable Rewards
2026年5月
SEAL: Synergistic Co-Evolution of Agents and Learning Environments
2025年12月
Let It Flow: Agentic Crafting on Rock and Roll, Building the ROME Model within an Open Agentic Learning Ecosystem
2025年11月
SkyRL-Agent: Efficient RL Training for Multi-turn LLM Agent
2025年9月
Planner-R1: Reward Shaping Enables Efficient Agentic RL with Smaller LLMs
2025年9月
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
2025年9月
Tree Search for LLM Agent Reinforcement Learning
2025年8月
Agent Lightning: Train ANY AI Agents with Reinforcement Learning
2025年7月
Agentic Reinforced Policy Optimization
2025年5月
Absolute Zero: Reinforced Self-play Reasoning with Zero Data
2025年5月
Group-in-Group Policy Optimization for LLM Agent Training
2025年4月
Agentic Reasoning and Tool Integration for LLMs via Reinforcement Learning
2025年4月
ToolRL: Reward is All Tool Learning Needs
2025年3月
ToRL: Scaling Tool-Integrated RL
2025年2月
Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search
2025年2月
SiriuS: Self-improving Multi-agent Systems via Bootstrapped Reasoning
2025年1月
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
2023年5月
Reasoning with Language Model is Planning with World Model
2023年5月
VOYAGER: An Open-Ended Embodied Agent with Large Language Models

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