Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.

MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model.

R-KV: Redundancy-aware KV Cache Compression for Reasoning Models

Official repository for EXAONE Deep built by LG AI Research

MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs

Official implementation of the paper "Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space"

Simple extension on vLLM to help you speed up reasoning model without training.

Official Repository of OmniCaptioner

xVerify: Efficient Answer Verifier for Reasoning Model Evaluations

Pivotal Token Search

[arXiv 2025] Can MLLMs Guide Me Home? A Benchmark Study on Fine-Grained Visual Reasoning from Transit Maps

Lightweight replication study of DeepSeek-R1-Zero. Interesting findings include "No Aha Moment", "Longer CoT ≠ Accuracy", and "Language Mixing in Instruct Models".

VeriThinker: Learning to Verify Makes Reasoning Model Efficient

Pure RL to post-train base models for social reasoning capabilities. Lightweight replication of DeepSeek-R1-Zero with Social IQa dataset.

An interactive thinking and deep reasoning model. It provides a cognitive reasoning paradigm for complex multi-hop problems.

Code for the 2025 ACL publication "Fine-Tuning on Diverse Reasoning Chains Drives Within-Inference CoT Refinement in LLMs"

This repository hosts the instructions and workshop materials for Lab 333 - Evaluate Reasoning Models for Your Generative AI Solutions

Using a reasoning LLM to learn a prompt from data

AI Lawyer is an intelligent reasoning legal assistant powered by DeepSeek , Ollama RAG and LangChain, designed to streamline legal research and document analysis. By leveraging retrieval-augmented generation (RAG), it provides precise legal insights, and contract summarization. With an intuitive Streamlit-based UI, analyze legal documents.

R1-Code-Interpreter: Training LLMs to Reason with Code via Supervised and Reinforcement Learning