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The official repo of SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
The official repo of MiniMax-Text-01 and MiniMax-VL-01, large-language-model & vision-language-model based on Linear Attention
Official MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.
SGLang is a fast serving framework for large language models and vision language models.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Efficient Triton Kernels for LLM Training
An Open-source RL System from ByteDance Seed and Tsinghua AIR
A Paper collection for LLM based Patient Simulators
Latest Advances on Long Chain-of-Thought Reasoning
Official resources of "The First Few Tokens Are All You Need: An Efficient and Effective Unsupervised Prefix Fine-Tuning Method for Reasoning Models"
Original implementation of SmartRAG: Jointly Learn RAG-Related Tasks From the Environment Feedback (ICLR 2025)
Pretraining code for a large-scale depth-recurrent language model
Automatically update arXiv papers about LLM Reasoning, LLM Evaluation, LLM & MLLM and Video Understanding using Github Actions.
verl: Volcano Engine Reinforcement Learning for LLMs
Finetune Qwen3, Llama 4, TTS, DeepSeek-R1 & Gemma 3 LLMs 2x faster with 70% less memory! 🦥
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
Medical o1, Towards medical complex reasoning with LLMs
Measuring Massive Multitask Language Understanding | ICLR 2021
[NAACL 2024 Outstanding Paper] Source code for the NAACL 2024 paper entitled "R-Tuning: Instructing Large Language Models to Say 'I Don't Know'"
[ACL 2025] Are Your LLMs Capable of Stable Reasoning?
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Implementation for the research paper "Enhancing LLM Reasoning via Critique Models with Test-Time and Training-Time Supervision".