Stars
Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models
Search-R1: An Efficient, Scalable RL Training Framework for Reasoning & Search Engine Calling interleaved LLM based on veRL
My learning notes/codes for ML SYS.
Democratizing Reinforcement Learning for LLMs
Fully open reproduction of DeepSeek-R1
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Project of ALC 2025 "UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on Large Language Models"
The group website repo for CUHK MoE Lab of High Confidence Software Technologies
[NeurIPS'24] Official code for *🎯DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving*
A Survey on the Honesty of Large Language Models
A collection of LLM papers, blogs, and projects, with a focus on OpenAI o1 🍓 and reasoning techniques.
Project of ACL 2025 MlingConf: A Comprehensive Investigation of Multilingual Confidence Estimation for Large Language Models
[ACL'24] Selective Reflection-Tuning: Student-Selected Data Recycling for LLM Instruction-Tuning
An Easy-to-use, Scalable and High-performance 9110 RLHF Framework based on Ray (PPO & GRPO & REINFORCE++ & vLLM & RFT & Dynamic Sampling & Async Agent RL)
Vite & Vue powered static site generator.
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
A modular graph-based Retrieval-Augmented Generation (RAG) system
雪之梦技术驿站,snowdreams1006搭建的 Gitbook 个人博客
A repo for open resources & information for people to succeed in PhD in CS & career in AI / NLP
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程
This is the repo which record the evolution of LM-based dialogue system. More details can be found in our original survey paper: A Survey of the Evolution of Language Model-Based Dialogue Systems
Existing Literature about Machine Unlearning