Pengfei Ding

According to our database, Pengfei Ding authored at least 15 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Cross-Domain Fake News Detection on Unseen Domains via LLM-Based Domain-Aware User Modeling.

Xuankai Yang, Yan Wang, Jiajie Zhu, Pengfei Ding, Hongyang Liu, Xiuzhen Zhang, Huan Liu

Proceedings of the ACM Web Conference 2026, 2026

MARCH: Multi-Teacher Contrastive Hypergraph Distillation.

Rongwei Xu, Zitai Qiu, Pengfei Ding, Jia Wu, Yan Wang, Amin Beheshti, Guanfeng Liu

Proceedings of the ACM Web Conference 2026, 2026

Re-understanding Graph Unlearning through Memorization.

Pengfei Ding, Yan Wang, Guanfeng Liu

Proceedings of the ACM Web Conference 2026, 2026

Adaptive and Reinforcement-Guided Contrastive Hypergraph Distillation.

Rongwei Xu, Zitai Qiu, Pengfei Ding, Yan Wang, Jia Wu, Amin Beheshti, Guanfeng Liu

Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, 2026

2025

Causal-Invariant Cross-Domain Out-of-Distribution Recommendation.

Jiajie Zhu, Yan Wang, Feng Zhu, Pengfei Ding, Hongyang Liu, Zhu Sun

CoRR, May, 2025

Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs.

Pengfei Ding, Yan Wang, Guanfeng Liu, Nan Wang, Xiaofang Zhou

IEEE Trans. Knowl. Data Eng., April, 2025

Towards Comprehensive and Prerequisite-Free Explainer for Graph Neural Networks.

Han Zhang, Yan Wang, Guanfeng Liu, Pengfei Ding, Huaxiong Wang, Kwok-Yan Lam

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Adaptive Graph Unlearning.

Pengfei Ding, Yan Wang, Guanfeng Liu, Jiajie Zhu

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Exploring Causal Relationships Across Shale Gas Wells: Granger Causality-Based Temporal Production Prediction.

Run Yang, Jiajie Zhu, Pengfei Ding, Yan Wang

Proceedings of the Advanced Data Mining and Applications - 21st International Conference, 2025

2024

Few-shot Learning on Heterogeneous Graphs: Challenges, Progress, and Prospects.

Pengfei Ding, Yan Wang, Guanfeng Liu

CoRR, 2024

Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs.

Pengfei Ding, Yan Wang, Guanfeng Liu, Nan Wang

CoRR, 2024

2023

Few-Shot Semantic Relation Prediction Across Heterogeneous Graphs.

Pengfei Ding, Yan Wang, Guanfeng Liu, Xiaofang Zhou

IEEE Trans. Knowl. Data Eng., October, 2023

A-MCTS: Adaptive Monte Carlo Tree Search for Temporal Path Discovery.

Pengfei Ding, Guanfeng Liu, Yan Wang, Kai Zheng, Xiaofang Zhou

IEEE Trans. Knowl. Data Eng., March, 2023

Cross-heterogeneity Graph Few-shot Learning.

Pengfei Ding, Yan Wang, Guanfeng Liu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2019

Reinforcement Learning Based Monte Carlo Tree Search for Temporal Path Discovery.

Pengfei Ding, Guanfeng Liu, Pengpeng Zhao, An Liu, Zhixu Li, Kai Zheng

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019