✨Data Intelligence Lab@HKU✨の公開GitHubフットプリント

Lightweight, open-source AI agent for your tools, chats, and workflows.

"CLI-Anything: Making ALL Software Agent-Native" -- CLI-Hub: https://clianything.cc/

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

DeepTutor: Agent-native, Open-sourced Personalized Tutoring. https://deeptutor.info/.

"RAG-Anything: All-in-One RAG Framework"

"AI-Trader: 100% Fully-Automated Agent-Native Trading"

"DeepCode: Open Agentic Coding (Paper2Code & Text2Web & Text2Backend)"

"OpenHarness: Open Agent Harness with a Built-in Personal Agent--Ohmo!"

"Vibe-Trading: Your Personal Trading Agent"

"ViMax: Agentic Video Generation (Director, Screenwriter, Producer, and Video Generator All-in-One)"

"AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework"

"ClawWork: OpenClaw as Your AI Coworker - 💰 $15K earned in 11 Hours"

"OpenSpace: Make Your Agents: Smarter, Low-Cost, Self-Evolving" -- Community: https://open-space.cloud/

[NeurIPS2025] "AI-Researcher: Autonomous Scientific Innovation" -- A production-ready version: https://novix.science/chat

"ClawTeam: Agent Swarm Intelligence" (One Command → Full Automation)

"Paper2Slides: From Paper to Presentation in One Click"

[KDD'2026] "VideoRAG: Chat with Your Videos"

"FastCode: Accelerating and Streamlining Your Code Understanding"

[ACL2026] "MiniRAG: Making RAG Simpler with Small and Open-Sourced Language Models"

"Your Fully-Automated Personal AI Assistant"

[SIGIR'2024] "GraphGPT: Graph Instruction Tuning for Large Language Models"

[ACL 2026] "OpenPhone: Mobile Agentic Foundation Models for AI Phone"

"VideoAgent: All-in-One Agentic Framework for Video Understanding, Editing, and Remaking"

"AnyTool: Universal Tool-Use Layer for AI Agents"

[ACL 2026 Oral] "LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?"

[ICML 2025] "SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator"

[WSDM'2024 Oral] "SSLRec: A Self-Supervised Learning Framework for Recommendation"

[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"

[WWW'2024] "RLMRec: Representation Learning with Large Language Models for Recommendation"

[KDD'2024] "UrbanGPT: Spatio-Temporal Large Language Models"

"CatchMe: Make Your AI Agents Truly Personal"

[KDD'2024] "LLM4Graph: A Survey of Large Language Models for Graphs"

[EMNLP2025] "GraphAgent: Agentic Graph Language Assistant"

[EMNLP'2024] "OpenGraph: Towards Open Graph Foundation Models"

"DeepInnovator: AI Research Assistant - Idea Spark & Scientific Discovery"

"AnyGraph: Graph Foundation Model in the Wild"

[WWW'2023] "MMSSL: Multi-Modal Self-Supervised Learning for Recommendation"

"MoChat: OpenClaw as Your Social Agent https://mochat.io"

[ICLR'2023] "LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation"

[EMNLP'2024] "XRec: Large Language Models for Explainable Recommendation"

"OpenCity: Open Spatio-Temporal Foundation Models for Traffic Prediction"

"FutureShow: Can AI Predict the Future? Live Real-World Forecasting"

"Litewrite: Vibe Writing is Coming - Write Faster and Better! https://litewrite.ai"

[EMNLP'2025] "EasyRec: Simple yet Effective Language Model for Recommendation"

[KDD'2024] "HiGPT: Heterogenous Graph Language Models"

"GraphEdit: Large Language Models for Graph Structure Learning"

[WSDM'2024 Oral] "DiffKG: Knowledge Graph Diffusion Model for Recommendation"

[WSDM'2023] "HGCL: Heterogeneous Graph Contrastive Learning for Recommendation"

[ACM CSUR] "A Comprehensive Survey of Self-Supervised Learning for Recommendation"

[ACL2025] "RecLM: Recommendation Instruction Tuning"

[ACM MM'2024]"DiffMM: Multi-Modal Diffusion Model for Recommendation"

[NeurIPS'2023] "GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks"

[ICML'2024] "FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction"

[CIKM'2024] "RecDiff: Diffusion Model for Social Recommendation"

[KDD'2023] "KGRec: Knowledge Graph Self-Supervised Rationalization for Recommendation"

[WWW'2024] "GraphPro: Graph Pre-training and Prompt Learning for Recommendation"

[WSDM'2025] "DiffGraph: Heterogeneous Graph Diffusion Model"

[SIGIR'2024] "SelfGNN: Self-Supervised Graph Neural Networks for Sequential Recommendation"

[SIGIR'2023] "GFormer: Graph Transformer for Recommendation"

[KDD'2023] "AdaGCL: Adaptive Graph Contrastive Learning for Recommendation"

[WWW'2023] "AutoST: Automated Spatio-Temporal Graph Contrastive Learning"

[SIGIR'2023] "MAERec: Graph Masked Autoencoder for Sequential Recommendation"

[WWW'2023] "DCRec: Debiased Contrastive Learning for Sequential Recommendation"

[SIGIR'2023] "DCCF: Disentangled Contrastive Collaborative Filtering"

[CIKM'2023] "STExplainer: Explainable Spatio-Temporal Graph Neural Networks"

[WSDM'25] "LightGNN: Simple Graph Neural Network for Recommendation"

[ICML'2023] "GraphST: Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation"

[ACM TIST] "LLM4Urban: Urban Computing in the Era of Large Language Models"

[EMNLP2025] "RecGPT: A Foundation Model for Sequential Recommendation"

"FastAgent: Simple, Fast, and Strong LLM Agents"

[WWW'2024] "PromptMM: Multi-Modal Knowledge Distillation for Recommendation with Prompt-Tuning"

[WWW'23] "AutoCF: Automated Self-Supervised Learning for Recommendation"

"DeepResearch-Eval: An End-to-End Evaluation Framework for DeepResearch Systems"

このリポジトリに関する説明は提供されていません。

Memory Governance Protocol

[IJCAI'2023] "DSL: Denoised Self-Augmented Learning for Social Recommendation"

[WWW'23] "SimRec: Graph-less Collaborative Filtering"

[CIKM'2023] "CL4ST: Spatio-Temporal Meta Contrastive Learning"

[ICDE'23] "DGNN: Disentangled Graph Social Recommendation"

[ICDE'2024] "GraphAug: Graph Augmentation for Recommendation"

[WSDM'2025] "MixRec: Heterogeneous Graph Collaborative Filtering"

[CIKM'2024] "EasyST: A Simple Framework for Spatio-Temporal Prediction"

[CIKM'2023] "GTE: How Expressive are Graph Neural Networks for Recommendation?"

[Recsys'2023] "RCL: Multi-Relational Contrastive Learning for Recommendation"

このリポジトリに関する説明は提供されていません。

このリポジトリに関する説明は提供されていません。

このリポジトリに関する説明は提供されていません。