Graph-COM

SubgraphRAG

[ICLR 2025] Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation

GraphMaker

[TMLR] GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?

GAD-NR

[WSDM 2024] GAD-NR : Graph Anomaly Detection via Neighborhood Reconstruction

ED-HNN

[ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li

LayerDAG

[ICLR 2025 Spotlight] LayerDAG: A Layerwise Autoregressive Diffusion Model of Directed Acyclic Graphs

HEPT

[ICML 2024 Oral] LSH-Based Efficient Point Transformer (HEPT)

SUREL

[VLDB'22] SUREL is a novel walk-based computation framework for efficient subgraph-based graph representation learning.

SPE

Official code for SPE

SUREL_Plus

[VLDB'23] SUREL+ is a novel set-based computation framework for scalable subgraph-based graph representation learning.

GESS

Code for GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts

LLM_BP

[ICML 2025] Generalization Principles for Inference over Text-Attributed Graphs with Large Language

Pair-Align

[ICML 2024] Code for Pairwise Alignment Improves Graph Domain Adaptation (Pair-Align)

GSSC

[Preprint] Graph State Space Convolution (GSSC)

GraphKV

Knowledge_Unlearning

xgdl

Explainability Library with Geometric Deep Learning for Scientific Tasks

EAPrivacy

EAPrivacy - Measuring Physical-World Privacy Awareness of Large Language Models: An Evaluation Benchmark

HaystackCraft

Haystack Engineering: Context Engineering for Heterogeneous and Agentic Long-Context Evaluation

Benchmark_for_DGRL_in_Hardwares

The official implementation of `A benchmark for Directed Graph Representation Learning in Hardware Designs'

GAD-EBM

[NeurIPS 2023 : GLFRONTIERS Workshop] GAD-EBM : Graph Anomaly Detection using Energy-Based Models

Langevin_unlearning

Minority_Aware_LLM_Unlearning

[ICML 2025] "Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning" Project

SGD_unlearning

TSA

Source code of "Structural Alignment Improves Graph Test-Time Adaptation"

Node_DP

Code for node DP of relation learning

PvGaLM

[COLM'25] PvGaLM is the first privacy-preserving relational learning pipeline that is compatible with DP-SGD.

Struc-Emb

RoFt-Mol

Code for the paper: RoFt-Mol: Benchmarking Robust Fine-Tuning with Molecular Graph Foundation Models

DP_GraphDiffusion

[NeurIPS 2024] Differentially Private Graph Diffusion with Applications in Personalized PageRanks

Walk_Profiles