Stars
RAGEN leverages reinforcement learning to train LLM reasoning agents in interactive, stochastic environments.
A live stream development of RL tunning for LLM agents
SkyRL-v0: Train Real-World Long-Horizon Agents via Reinforcement Learning
verl: Volcano Engine Reinforcement Learning for LLMs
Democratizing Reinforcement Learning for LLMs
TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios
Scaling Deep Research via Reinforcement Learning in Real-world Environments.
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas…
A Comprehensive Benchmark to Evaluate LLMs as Agents (ICLR'24)
Code for the paper "FinRL-DeepSeek: LLM-Infused Risk-Sensitive Reinforcement Learning for Trading Agents" arXiv:2502.07393
Data and code for EMNLP 2021 paper "FinQA: A Dataset of Numerical Reasoning over Financial Data"
Official repository of ’Visual-RFT: Visual Reinforcement Fine-Tuning’
Search-R1: An Efficient, Scalable RL Training Framework for Reasoning & Search Engine Calling interleaved LLM based on veRL
Minimal reproduction of DeepSeek R1-Zero
[EMNLP 2024 Findings] OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs.
SGLang is a fast serving framework for large language models and vision language models.
A guidance language for controlling large language models.