Short Bio
I am a Ph.D. student at The Chinese University of Hong Kong, under the supervision of Prof. Hong CHENG.
Previously, I received my B.S. and M.S. in Computer Science from Fudan University in 2021 and 2024, respectively.
I was a Research Intern at Microsoft Research Asia (Shanghai AI/ML Group), mentored by Dr. Yifei SHEN and Dr. Caihua SHAN.
My research interests lie in the intersection of Graph Learning and Large Language Models (LLMs). Specifically, I focus on integrating Graph Learning with LLMs to enhance their reasoning capabilities in graph-related applications, such as task planning in autonomous agents. Additionally, I am interested in Data Mining, focusing on topics like community detection, graph prompt learning, recommender systems, etc.
Research Highlights
-
Graph Learning for Task Planning (NeurIPS'2024)
In language agents, available tasks naturally form a task graph, where nodes represent tasks and edges denote dependencies. Under such context, task planning involves selecting a path within this graph to fulfill user requests. We find that the bottleneck in LLMs' planning abilities lies in their limited understanding of the task graph. Therefore, we introduce GNNs as a simple fix, available in both training-free and training-required variants. Extensive experiments demonstrate that GNN-based methods surpass existing solutions even without training.
-
Graph Prompt Learning
Graph Prompt Learning (GPL) focuses on adapting pre-trained graph models to downstream tasks by manipulating downstream data to align with pre-training objectives. Our research includes (1) A comprehensive survey of existing graph prompt learning methods (under the supervision of Dr. Xiangguo Sun), and (2) Application of GPL techniques to various scenarios including Targeted Community Detection (SIGKDD'2024), Temporal Interaction Graph Modeling, and Drug-Drug-Interaction Event Prediction (CIKM'2024).
Selected Publications
-
Can Graph Learning Improve Planning in LLM-based Agents?
Xixi Wu, Yifei Shen, Caihua Shan, Kaitao Song, Siwei Wang, Bohang Zhang, Jiarui Feng, Hong Cheng, Wei Chen, Yun Xiong, and Dongsheng Li
To appear, Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS), 2024
-
ProCom: A Few-shot Targeted Community Detection Algorithm
Xixi Wu, Kaiyu Xiong, Yun Xiong, Xiaoxin He, Yao Zhang, Yizhu Jiao, and Jiawei Zhang
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024
-
ConsRec: Learning Consensus Behind Interactions for Group Recommendation
Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang, Yangyong Zhu, and Philip S. Yu
Proceedings of the ACM Web Conference (WWW), 2023
-
CLARE: A Semi-supervised Community Detection Algorithm
Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Caihua Shan, Yiheng Sun, Yangyong Zhu, and Philip S. Yu
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022
-
DDIPrompt: Drug-Drug Interaction Event Prediction based on Graph Prompt Learning
Yingying Wang, Yun Xiong, Xixi Wu, Xiangguo Sun, Jiawei Zhang, and Guangyong Zheng
To appear, Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM), 2024
-
Towards Adaptive Neighborhood for Advancing Temporal Interaction Graph Modeling
Siwei Zhang, Xi Chen, Yun Xiong, Xixi Wu, Yao Zhang, Yongrui Fu, Yinglong Zhao, and Jiawei Zhang
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024
-
Dual Intents Graph Modeling for User-centric Group Discovery
Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, and Jiawei Zhang
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM), 2023
-
iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation
Siwei Zhang, Yun Xiong, Yao Zhang, Xixi Wu, Yiheng Sun, and Jiawei Zhang.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM), 2023
Experience
-
Microsoft Research Asia
Research Intern, Shanghai AI/ML Group Feb. 2024 - Jun. 2024
-
Microsoft
Software Engineer Intern, Outlook Mobile Team Jul. 2020 - Sep. 2020
Selected Awards
- National Scholarship for Graduate Student, Ministry of Education, China 2022 & 2023
- ACM Web Conference Student Travel Award 2023
- Second Class Scholarship for Outstanding Student, Fudan University 2018 & 2021
- Second Prize of Undergraduate Mathematical Contest in Modeling, Shanghai, China (CUMCM) 2019
- First Prize in National Olympiad in Mathematics in Provinces, Jiangsu, China 2016
Professional Services
- Conference Reviewer: WWW'2024 Graph Foundation Model (GFM) Workshop, SIGKDD'2024&2025, NeurIPS'2024, ICLR'2025
- Journal Reviewer: TKDE
- Oral Presentation: WWW'2023
Miscellaneous
- I love sports like swimming 🏊 and running 🏃. I also enjoy cooking Chinese food 🤣
- During my undergraduate studies, I was interested in mobile app development (You can find all the source codes on my GitHub):
Lose Weight, a Fluter App
Hulv, a Mini-Program
Chatroom, a Desktop App
- I enjoy exploring the unknown and strive to keep moving forward on this path of discovery and learning ✨
