25 open source projects by THUDM

Source code and dataset for IJCAI 2019 paper "ProNE: Fast and Scalable Network Representation Learning"

Paper list of NLP for recommender systems

Source code and dataset for KDD 2019 paper "Towards Knowledge-Based Personalized Product Description Generation in E-commerce"

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

Source code and dataset for KDD 2020 paper "Controllable Multi-Interest Framework for Recommendation"

Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"

Implementation of "GraphSGAN", a GAN-based semi-supervised learning algorithm for graph data.

CogDL: An Extensive Research Toolkit for Graphs

Source code and dataset for ACL 2019 paper "Cognitive Graph for Multi-Hop Reading Comprehension at Scale"

Source code and dataset for KDD 2019 paper "Representation Learning for Attributed Multiplex Heterogeneous Network"

Text-to-Image generation. The repo for NeurIPS 2021 paper "CogView: Mastering Text-to-Image Generation via Transformers".

Source code and dataset for paper "Cognitive Knowledge Graph Reasoning for One-shot Relational Learning"

Source code and data for ACL 2022 paper "P-tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks"

No description, website, or topics provided.

Source code and dataset for TKDE 2019 paper “Trust Relationship Prediction in Alibaba E-Commerce Platform”

GLM (General Language Model)

Graph Injection Adversarial Attack & Defense Dataset , extracted from KDD CUP 2020 ML2 Track

Protein Language Model

Towards Knowledge-Based Recommender Dialog System @ EMNLP 2019

Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.

Source code and dataset for KDD 2019 paper "OAG: Toward Linking Large-scale Heterogeneous Entity Graphs"

No description, website, or topics provided.

A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.

Source code and dataset for KDD 2019 paper "Sequential Scenario-Specific Meta Learner for Online Recommendation"

Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.