AI Agent Skills

The implementation of "TabR: Unlocking the Power of Retrieval-Augmented Tabular Deep Learning"

Official PyTorch implementation of the paper: "DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample" (ICCV 2021 Oral)

Cognitive architecture for AI-augmented software development. Specialized agents, structured workflows, and multi-platform deployment. Claude Code · Codex · Copilot · Cu…

A framework for fine-tuning retrieval-augmented generation (RAG) systems.

A Blazor Web App and Minimal API for performing RAG (Retrieval Augmented Generation) and vector search using the native VECTOR type in Azure SQL Database and Azure OpenA…

XRAG: eXamining the Core - Benchmarking Foundational Component Modules in Advanced Retrieval-Augmented Generation

Retrieval-Augmented Theorem Provers for Lean

GibRAM is an in-memory knowledge graph server designed for retrieval augmented generation (RAG / GraphRAG) workflows.

[KDD 2026] MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation

Open-source document chat platform with semantic search, RAG (Retrieval Augmented Generation), and multi-provider AI support (OpenRouter, OpenAI, ImageRouter).

🔍 Deep RAG: Advanced Retrieval-Augmented Generation system that goes beyond vector search. Enables AI to perform multi-hop reasoning, negation queries, numerical compar…

CrawlAI RAG is an AI-powered website intelligence platform that allows users to crawl entire websites, index their content, and ask natural-language questions using Retr…

An interactive visualization tool for understanding Retrieval-Augmented Generation (RAG) pipelines.

Launching the "Agent Creation Toolkit", providing developers with an intuitive and efficient Development Environment, supporting the rapid construction of intelligent ag…

This RAG (Retrieval-Augmented Generation) project is implemented using pure Java. This approach makes it easier to adapt to enterprise-level environments and is more con…

[EMNLP 2024] LongRAG: A Dual-perspective Retrieval-Augmented Generation Paradigm for Long-Context Question Answering