HKUDS
👨💻 Welcome to the Data Intelligence Lab! We are a team of dedicated researchers who specialize Data Science at the University of Hong Kong 📚
University of Hong KongHong Kong
Pinned Repositories
GraphEdit
"GraphEdit: Large Language Models for Graph Structure Learning"
GraphGPT
[SIGIR'2024] "GraphGPT: Graph Instruction Tuning for Large Language Models"
HGCL
[WSDM'2023] "HGCL: Heterogeneous Graph Contrastive Learning for Recommendation"
LightGCL
[ICLR'2023] "LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation"
LLMRec
[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"
MMSSL
[WWW'2023] "MMSSL: Multi-Modal Self-Supervised Learning for Recommendation"
OpenGraph
"OpenGraph: Towards Open Graph Foundation Models"
RLMRec
[WWW'2024] "RLMRec: Representation Learning with Large Language Models for Recommendation"
SSLRec
[WSDM'2024 Oral] "SSLRec: A Self-Supervised Learning Framework for Recommendation"
UrbanGPT
[KDD'2024] "UrbanGPT: Spatio-Temporal Large Language Models"
HKUDS's Repositories
HKUDS/GraphGPT
[SIGIR'2024] "GraphGPT: Graph Instruction Tuning for Large Language Models"
HKUDS/SSLRec
[WSDM'2024 Oral] "SSLRec: A Self-Supervised Learning Framework for Recommendation"
HKUDS/LLMRec
[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"
HKUDS/RLMRec
[WWW'2024] "RLMRec: Representation Learning with Large Language Models for Recommendation"
HKUDS/OpenGraph
"OpenGraph: Towards Open Graph Foundation Models"
HKUDS/UrbanGPT
[KDD'2024] "UrbanGPT: Spatio-Temporal Large Language Models"
HKUDS/MMSSL
[WWW'2023] "MMSSL: Multi-Modal Self-Supervised Learning for Recommendation"
HKUDS/GraphEdit
"GraphEdit: Large Language Models for Graph Structure Learning"
HKUDS/HiGPT
[KDD'2024] "HiGPT: Heterogenous Graph Language Models"
HKUDS/Awesome-SSLRec-Papers
A Comprehensive Survey of Self-Supervised Learning for Recommendation
HKUDS/Awesome-LLM4Graph-Papers
[KDD'2024 Survey+Tutorial] "LLM4Graph: A Survey of Large Language Models for Graphs"
HKUDS/DiffKG
[WSDM'2024 Oral] "DiffKG: Knowledge Graph Diffusion Model for Recommendation"
HKUDS/GPT-ST
[NeurIPS'2023] "GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks"
HKUDS/GFormer
[SIGIR'2023] "GFormer: Graph Transformer for Recommendation"
HKUDS/KGRec
[KDD'2023] "KGRec: Knowledge Graph Self-Supervised Rationalization for Recommendation"
HKUDS/AdaGCL
[KDD'2023] "AdaGCL: Adaptive Graph Contrastive Learning for Recommendation"
HKUDS/DCCF
[SIGIR'2023] "DCCF: Disentangled Contrastive Collaborative Filtering"
HKUDS/AutoCF
[WWW'23] "AutoCF: Automated Self-Supervised Learning for Recommendation"
HKUDS/XRec
"XRec: Large Language Models for Explainable Recommendation"
HKUDS/GraphPro
[WWW'2024] "GraphPro: Graph Pre-training and Prompt Learning for Recommendation"
HKUDS/GraphST
[ICML'2023] "GraphST: Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation"
HKUDS/PromptMM
[WWW'2024] "PromptMM: Multi-Modal Knowledge Distillation for Recommendation with Prompt-Tuning"
HKUDS/STExplainer
[CIKM'2023] "STExplainer: Explainable Spatio-Temporal Graph Neural Networks"
HKUDS/FlashST
[ICML'2024] "FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction"
HKUDS/RecDiff
"RecDiff: Diffusion Model for Social Recommendation"
HKUDS/DSL
[IJCAI'2023] "DSL: Denoised Self-Augmented Learning for Social Recommendation"
HKUDS/CL4ST
[CIKM'2023] "CL4ST: Spatio-Temporal Meta Contrastive Learning"
HKUDS/GraphAug
[ICDE'2024] "GraphAug: Graph Augmentation for Recommendation"
HKUDS/SelfGNN
[SIGIR'2024] "SelfGNN: Self-Supervised Graph Neural Networks for Sequential Recommendation"
HKUDS/HKUDS