Yongduo Sui
Scholar

Yongduo Sui

Google Scholar ID: VD9g6ogAAAAJ
Tencent
LLMAgentGraph LearningRecommendation
Homepage↗Google Scholar↗
Citations & Impact
All-time
Citations
4,022
 
H-index
15
 
i10-index
17
 
Publications
20
 
Co-authors
2
list available
Contact
GitHubOpen ↗
Publications
4 items
Multi-turn Training with Basic Human Feedback Helps Little on LLM Reasoning
2025
Cited
0
Unleashing the Power of Large Language Model for Denoising Recommendation
2025
Cited
0
A Unified Invariant Learning Framework for Graph Classification
2025
Cited
0
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
arXiv.org · 2024
Cited
2
Resume (English only)
Academic Achievements
  • - Publications in 2025:
  • - Two full papers accepted by WWW'25 on LLM-based recommendation and graph generalization
  • - One full paper accepted by KDD'25 on graph OOD generalization
  • - Publications in 2024:
  • - Five full papers accepted by WWW'24 on invariant graph learning, KG-recommendation, graph condensation, and graph anomaly detection
  • - One full paper accepted by ICML'24 on boosting graph sparse training via semantic and topological awareness
  • - Publications in 2023 and before:
  • - Multiple full papers accepted by ICDE'24, WSDM'24, NeurIPS'23, WWW'23, and KDD'22 on various topics including graph contrastive learning, efficient recommendation, and graph unlearning
Research Experience
  • - Research Intern, Ant Group, Hangzhou, March 2023 - June 2024, Mentors: Jun Zhou, Longfei Li, and Qing Cui
Education
  • - PhD in Computer Science, University of Science and Technology of China (USTC), Sep 2021 - June 2024, Advisors: Prof. Xiangnan He and Prof. Xiang Wang
  • - Master in Computer Science, University of Science and Technology of China (USTC), Sep 2019 - June 2021, Advisor: Prof. Bin Li
  • - Bachelor in Electrical Engineering, Harbin Engineering University (HEU), Sep 2015 - June 2019
Background
  • - Research Interests: Large Language Models (LLM), Agent-based systems, Graph Learning, and Recommendation Systems
  • - Professional Field: Computer Science
  • - Brief Introduction: Currently a Senior Researcher at Tencent, having recently completed his PhD at the Lab for Data Science, University of Science and Technology of China (USTC), under the supervision of Prof. Xiangnan He and Prof. Xiang Wang. During his PhD, he focused on Out-of-distribution Generalization, Self-supervised Learning, Causal Inference, and Efficient Machine Learning, with a particular emphasis on Graph Learning and Recommendation Systems.
Co-authors
2 total
Xiang Wang
Xiang Wang
University of Science and Technology of China
Xiangnan He
Xiangnan He
University of Science and Technology of China