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Meta Agents Research Environments is a comprehensive platform designed to evaluate AI agents in dynamic, realistic scenarios. Unlike static benchmarks, this platform introduces evolving environment…
verl-agent is an extension of veRL, designed for training LLM/VLM agents via RL. verl-agent is also the official code for paper "Group-in-Group Policy Optimization for LLM Agent Training"
Meridian cuts through news noise by scraping hundreds of sources, analyzing stories with AI, and delivering concise, personalized daily briefs.
Our library for RL environments + evals
Minimal reproduction of DeepSeek R1-Zero
verl: Volcano Engine Reinforcement Learning for LLMs
Search-R1: An Efficient, Scalable RL Training Framework for Reasoning & Search Engine Calling interleaved LLM based on veRL
RAGEN leverages reinforcement learning to train LLM reasoning agents in interactive, stochastic environments.
Automate browser based workflows with AI
An elegant PyTorch deep reinforcement learning library.
A toolkit for reproducible reinforcement learning research.
Official implementation of the AAAI 2021 paper Deep Bayesian Quadrature Policy Optimization.