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The Chinese University of Hong Kong, Shenzhen
- China
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05:42
(UTC +08:00) - http://profile.aoyangfang.top/
- https://orcid.org/0009-0006-7116-5613
Highlights
- Pro
Stars
🏡 GitHub Pages template for personal academic homepage
(Minimalism Style) Powered by Jekyll, based on the Minimal Mistakes theme and Jason Ansel's website
A project page template for academic papers. Demo at https://eliahuhorwitz.github.io/Academic-project-page-template/
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
A simple yet powerful agent framework that delivers with open-source models
⚡ Hugo Blox: Markdown sites in minutes. Academic/resume/lab/portfolio for AI researchers & startups. Premium templates. Deploy to GitHub Pages now in 1-click 👇
Democratizing Reinforcement Learning for LLMs
[NeurIPS'25] Official Implementation of RISE (Reinforcing Reasoning with Self-Verification)
🎉 A Vue.js 3 UI Library made by Element team
SkyRL: A Modular Full-stack RL Library for LLMs
RAGEN leverages reinforcement learning to train LLM reasoning agents in interactive, stochastic environments.
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
[ICLR'25] OpenRCA: Can Large Language Models Locate the Root Cause of Software Failures?
Agent-R1: Training Powerful LLM Agents with End-to-End Reinforcement Learning
JS snippet to send codeblock contents as a query string
verl: Volcano Engine Reinforcement Learning for LLMs
ReCall: Learning to Reason with Tool Call for LLMs via Reinforcement Learning
R1-searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible.
Data and Code for EMNLP 2025 Findings Paper "MCTS-RAG: Enhancing Retrieval-Augmented Generation with Monte Carlo Tree Search"
🔥 The Web Data API for AI - Turn entire websites into LLM-ready markdown or structured data
Writing AI Conference Papers: A Handbook for Beginners
An Easy-to-use, Scalable and High-performance RLHF Framework based on Ray (PPO & GRPO & REINFORCE++ & vLLM & Ray & Dynamic Sampling & Async Agentic RL)