AutoSchemaKG alternatives for AI agents.

Collect, organize, use, and share, all in OmniBox.

Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.

Daily updated LLM papers. 每日更新 LLM 相关的论文，欢迎订阅 👏 喜欢的话动动你的小手 🌟 一个

KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.

Official Repo for "TheoremExplainAgent: Towards Video-based Multimodal Explanations for LLM Theorem Understanding" [ACL 2025 oral]

[ICLR 2026] Youtu-GraphRAG: Vertically Unified Agents for Graph Retrieval-Augmented Complex Reasoning

TrustRAG：The RAG Framework within Reliable input,Trusted output

Ingest files for retrieval augmented generation (RAG) with open-source Large Language Models (LLMs), all without 3rd parties or sensitive data leaving your network.

This NVIDIA RAG blueprint serves as a reference solution for a foundational Retrieval Augmented Generation (RAG) pipeline.

[EMNLP'25 findings] This is the official repo for the paper, HiRAG: Retrieval-Augmented Generation with Hierarchical Knowledge.

[ICLR 2026] LinearRAG: Linear Graph Retrieval Augmented Generation on Large-scale Corpora

A project-based course repository for developing AI agents using LangChain v1+ and LangGraph: search agents, RAG systems, reflection agents, and code interpreters.

A toolkit to create optimal Production-readyRetrieval Augmented Generation(RAG) setup for your data

[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"

[NeurIPS '25] Knowledge Graph Generation from Any Text

WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus.