The repository implements the Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification

This is the official github repo of Think-on-Graph. If you are interested in our work or willing to join our research team in Shenzhen, please feel free to contact us by email (xuchengjin@idea.edu.cn)

This project aims to collect the latest "call for reviewers" links from various top CS/ML/AI conferences/journals

Official implementation for Zhong & Le et al., GNNs Also Deserve Editing, and They Need It More Than Once. ICML 2024

Codes and data for KDD 2024 Research Track paper "ProCom: A Few-shot Targeted Community Detection Algorithm"

PyGDA is a Python library for Graph Domain Adaptation

Create Customized Software using Natural Language Idea (through LLM-powered Multi-Agent Collaboration)

🐝 GPTSwarm: LLM agents as (Optimizable) Graphs

A list of papers that studies Novel Class Discovery

A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.

LLM for Drug Editing, ICLR 2024

[SIGKDD 2024] Rethinking Fair Graph Neural Networks from Re-balancing

[ICML'24] BAT: 🚀 Boost Class-imbalanced Node Classification with <10 lines of Code | 从拓扑视角出发10行代码改善类别不平衡节点分类

Code for IJCAI'24 paper: Gradformer: Graph Transformer with Exponential Decay

The official implement of SIGKDD'24 paper: ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs

Collecting awesome papers of RAG for AIGC. We propose a taxonomy of RAG foundations, enhancements, and applications in paper "Retrieval-Augmented Generation for AI-Generated Content: A Survey".

Forward-Looking Active REtrieval-augmented generation (FLARE)

This includes the original implementation of SELF-RAG: Learning to Retrieve, Generate and Critique through self-reflection by Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi.

✨✨Latest Advances on Multimodal Large Language Models

The collection of resources about LLM for Time series tasks

Continual Learning of Large Language Models: A Comprehensive Survey

Must-read Papers on Knowledge Editing for Large Language Models.

[EMNLP 2023] MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions

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

A curated list of awesome papers on dataset distillation and related applications.

[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.