Gen-Verse/OpenClaw-RL
OpenClaw-RL: Train any agent simply by talking
Democratizing Reinforcement Learning for LLMs
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Agent instructions and tool configuration found in this repository.
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OpenClaw-RL: Train any agent simply by talking
slime is an LLM post-training framework for RL Scaling.
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Awesome resources for in-context learning and prompt engineering: Mastery of the LLMs such as ChatGPT, GPT-3, and FlanT5, with up-to-date and cutting-edge updates.
The paper list of the 86-page SCIS cover paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.
GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models