Zehong Wang
Portrait
Ph.D. Candidate
Computer Science and Engineering
Logo University of Notre Dame

I am a fourth year Ph.D. student (2023 Fall - Present) in Computer Science and Engineering at University of Notre Dame advised by Prof. Yanfang (Fanny) Ye. My research focuses on developing generalizable AI systems that integrate multimodal data for scientific discovery. Recently, I have been working on scientific foundation models and AI agents, with the goal of building AI scientists for drug discovery and public health.

Feel free to reach out me via email, wechat, or linkedin if you have any questions, explore potential collaborations, or just for talk! 😊

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News
2026
One paper accepted to NeurIPS 2026.
Sep 27
Three papers accepted to EMNLP 2026.
Aug 19
One paper accepted to COLM 2026.
Jul 13
Two papers accepted to KDD 2026.
May 14
💼 I will join Google as a Research Intern.
May 10
Four papers accepted to ICML 2026.
Apr 30
One paper accepted to ACL 2026.
Apr 07
📚 Our survey on weight space learning is released.
Mar 09
One paper accepted to WWW 2026. This is my first corresponding paper 😊.
Jan 12
One paper accepted to EACL 2026.
Jan 03
2025
📚 Our survey on LLM for cross-disciplinary research is released.
Sep 22
Two papers accepted to NeurIPS 2025.
Sep 19
💼 I will join Amazon as Applied Scientist Intern working with Prof. Rui Song, Prof. Sheng Wang and Dr. Qingkai Zeng.
May 21
📚 Our survey on graph foundation model is released.
May 20
Two papers accepted to ACL 2025.
May 14
📖 Two tutorials accepted to KDD 25 (graph foundation model and graph prompt learning).
May 05
Two papers accepted to ICML 2025.
Apr 30
One paper accepted to NAACL 2025.
Jan 21
2024
One paper accepted to KDD 2025.
Nov 14
One paper accepted to WSDM 2025.
Oct 22
One paper accepted to NeurIPS 2024.
Sep 14
One paper accepted to KDD 2024.
May 15
One paper accepted to IJCAI 2024.
Apr 14
Receive the Travel Award Grand from SDM 2024. Thanks SDM!
Mar 14
Selected Publications (view all )
The Collaboration Tax: How Much LLM Multi-Agent Systems Pay to Coordinate
The Collaboration Tax: How Much LLM Multi-Agent Systems Pay to Coordinate

Weixiang Sun, Zehong Wang, Hong Huang, Colby Nelson, Yijun Ma, Yanfang Ye ( corresponding author)

Conference on Empirical Methods in Natural Language Processing (EMNLP) 2026

[Paper] [Code]

The Collaboration Tax: How Much LLM Multi-Agent Systems Pay to Coordinate

Weixiang Sun, Zehong Wang, Hong Huang, Colby Nelson, Yijun Ma, Yanfang Ye ( corresponding author)

Conference on Empirical Methods in Natural Language Processing (EMNLP) 2026

[Paper] [Code]

MDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback
MDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback

Zehong Wang, Yijun Ma, Connor R. Schmidt, Tianyi Ma, Weixiang Sun, Ziming Li, Xiaoguang Guo, Chuxu Zhang, Matthew J. Webber, Yanfang Ye

Conference on Empirical Methods in Natural Language Processing (EMNLP) 2026

[Paper] [Code]

MDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback

Zehong Wang, Yijun Ma, Connor R. Schmidt, Tianyi Ma, Weixiang Sun, Ziming Li, Xiaoguang Guo, Chuxu Zhang, Matthew J. Webber, Yanfang Ye

Conference on Empirical Methods in Natural Language Processing (EMNLP) 2026

[Paper] [Code]

W2T: LoRA Weights Already Know What They Can Do
W2T: LoRA Weights Already Know What They Can Do

Xiaolong Han, Ferrante Neri, Zijian Jiang, Fang Wu, Yanfang Ye, Lu Yin, Zehong Wang ( corresponding author)

Conference on Empirical Methods in Natural Language Processing (EMNLP) 2026

[Paper] [Code]

W2T: LoRA Weights Already Know What They Can Do

Xiaolong Han, Ferrante Neri, Zijian Jiang, Fang Wu, Yanfang Ye, Lu Yin, Zehong Wang ( corresponding author)

Conference on Empirical Methods in Natural Language Processing (EMNLP) 2026

[Paper] [Code]

ProPlay: Procedural World Models for Self-Evolving LLM Agents
ProPlay: Procedural World Models for Self-Evolving LLM Agents

Yijun Ma*, Zehong Wang*, Yiyang Li, Ziming Li, Xiaoguang Guo, Weixiang Sun, Chuxu Zhang, Yanfang Ye (* equal contribution, corresponding author)

arXiv preprint 2026

[Paper] [Code]

ProPlay: Procedural World Models for Self-Evolving LLM Agents

Yijun Ma*, Zehong Wang*, Yiyang Li, Ziming Li, Xiaoguang Guo, Weixiang Sun, Chuxu Zhang, Yanfang Ye (* equal contribution, corresponding author)

arXiv preprint 2026

[Paper] [Code]

SupraBench: A Benchmark for Supramolecular Chemistry
SupraBench: A Benchmark for Supramolecular Chemistry

Tianyi Ma, Yijun Ma, Zehong Wang, Weixiang Sun, Ziming Li, Connor R. Schmidt, Chuxu Zhang, Matthew J. Webber, Yanfang Ye ( corresponding author)

arXiv preprint 2026

[Paper] [Code]

SupraBench: A Benchmark for Supramolecular Chemistry

Tianyi Ma, Yijun Ma, Zehong Wang, Weixiang Sun, Ziming Li, Connor R. Schmidt, Chuxu Zhang, Matthew J. Webber, Yanfang Ye ( corresponding author)

arXiv preprint 2026

[Paper] [Code]

Hypergraph Pattern Machine: Compositional Tokenization for Higher-Order Interactions
Hypergraph Pattern Machine: Compositional Tokenization for Higher-Order Interactions

Kyrie Zhao*, Zehong Wang*, Tianyi Ma, Fang Wu, Xiangru Tang, Pietro Lio, Sheng Wang, Yanfang Ye (* equal contribution, corresponding author)

arXiv preprint 2026

[Paper] [Code]

Hypergraph Pattern Machine: Compositional Tokenization for Higher-Order Interactions

Kyrie Zhao*, Zehong Wang*, Tianyi Ma, Fang Wu, Xiangru Tang, Pietro Lio, Sheng Wang, Yanfang Ye (* equal contribution, corresponding author)

arXiv preprint 2026

[Paper] [Code]

A Survey of Weight Space Learning: Understanding, Representation, and Generation
A Survey of Weight Space Learning: Understanding, Representation, and Generation

Xiaolong Han*, Zehong Wang*, Bo Zhao, Binchi Zhang, Jundong Li, Damian Borth, Rose Yu, Haggai Maron, Yanfang Ye, Lu Yin, Ferrante Neri (* equal contribution, corresponding author)

arXiv preprint 2026 Survey

[Paper] [Repo]

A Survey of Weight Space Learning: Understanding, Representation, and Generation

Xiaolong Han*, Zehong Wang*, Bo Zhao, Binchi Zhang, Jundong Li, Damian Borth, Rose Yu, Haggai Maron, Yanfang Ye, Lu Yin, Ferrante Neri (* equal contribution, corresponding author)

arXiv preprint 2026 Survey

[Paper] [Repo]

Temporal Graph Pattern Machine
Temporal Graph Pattern Machine

Yijun Ma*, Zehong Wang*, Weixiang Sun, Yanfang Ye (* equal contribution, corresponding author)

GFM @ ICML Workshop (Oral) 2026

[Paper] [Code]

Temporal Graph Pattern Machine

Yijun Ma*, Zehong Wang*, Weixiang Sun, Yanfang Ye (* equal contribution, corresponding author)

GFM @ ICML Workshop (Oral) 2026

[Paper] [Code]

Molecular Representations in Implicit Functional Space via Hyper-Networks
Molecular Representations in Implicit Functional Space via Hyper-Networks

Zehong Wang*, Xiaolong Han*, Qi Yang*, Xiangru Tang, Fang Wu, Xiaoguang Guo, Weixiang Sun, Tianyi Ma, Pietro Lio, Le Cong, Sheng Wang, Chuxu Zhang, Yanfang Ye (* equal contribution)

arXiv preprint 2026

[Paper] [Code]

Molecular Representations in Implicit Functional Space via Hyper-Networks

Zehong Wang*, Xiaolong Han*, Qi Yang*, Xiangru Tang, Fang Wu, Xiaoguang Guo, Weixiang Sun, Tianyi Ma, Pietro Lio, Le Cong, Sheng Wang, Chuxu Zhang, Yanfang Ye (* equal contribution)

arXiv preprint 2026

[Paper] [Code]

Why Reasoning Fails to Plan: A Planning-Centric Analysis of Long-Horizon Decision Making in LLM Agents
Why Reasoning Fails to Plan: A Planning-Centric Analysis of Long-Horizon Decision Making in LLM Agents

Zehong Wang, Fang Wu, Hongru Wang, Xiangru Tang, Bolian Li, Zhenfei Yin, Yijun Ma, Yiyang Li, Weixiang Sun, Xiusi Chen, Yanfang Ye

arXiv preprint 2026

[Paper] [Code]

Why Reasoning Fails to Plan: A Planning-Centric Analysis of Long-Horizon Decision Making in LLM Agents

Zehong Wang, Fang Wu, Hongru Wang, Xiangru Tang, Bolian Li, Zhenfei Yin, Yijun Ma, Yiyang Li, Weixiang Sun, Xiusi Chen, Yanfang Ye

arXiv preprint 2026

[Paper] [Code]

Controllable Graph Generation with Diffusion Models via Inference-Time Tree Search Guidance
Controllable Graph Generation with Diffusion Models via Inference-Time Tree Search Guidance

Jiachi Zhao*, Zehong Wang*, Yamei Liao, Chuxu Zhang, Yanfang Ye (* equal contribution, corresponding author)

The Web Conference (WWW) (Oral) 2026

[Paper] [Code]

Controllable Graph Generation with Diffusion Models via Inference-Time Tree Search Guidance

Jiachi Zhao*, Zehong Wang*, Yamei Liao, Chuxu Zhang, Yanfang Ye (* equal contribution, corresponding author)

The Web Conference (WWW) (Oral) 2026

[Paper] [Code]

Semantic Refinement with LLMs for Graph Representations
Semantic Refinement with LLMs for Graph Representations

Safal Thapaliya*, Zehong Wang*, Jiazheng Li, Ziming Li, Yanfang Ye, Chuxu Zhang (* equal contribution)

arXiv preprint 2025

[Paper] [Code]

Semantic Refinement with LLMs for Graph Representations

Safal Thapaliya*, Zehong Wang*, Jiazheng Li, Ziming Li, Yanfang Ye, Chuxu Zhang (* equal contribution)

arXiv preprint 2025

[Paper] [Code]

Generative Graph Pattern Machine
Generative Graph Pattern Machine

Zehong Wang, Zheyuan Zhang, Tianyi Ma, Chuxu Zhang, Yanfang Ye

Annual Conference on Neural Information Processing Systems (NeurIPS) 2025

[Paper] [Code]

Generative Graph Pattern Machine

Zehong Wang, Zheyuan Zhang, Tianyi Ma, Chuxu Zhang, Yanfang Ye

Annual Conference on Neural Information Processing Systems (NeurIPS) 2025

[Paper] [Code]

Beyond Message Passing: Neural Graph Pattern Machine
Beyond Message Passing: Neural Graph Pattern Machine

Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye

International Conference on Machine Learning (ICML) 2025

[Paper] [Code]

Beyond Message Passing: Neural Graph Pattern Machine

Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye

International Conference on Machine Learning (ICML) 2025

[Paper] [Code]

Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees
Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees

Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye

International Conference on Machine Learning (ICML) 2025

[Paper] [Code]

Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees

Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye

International Conference on Machine Learning (ICML) 2025

[Paper] [Code]

Graph Foundation Models: A Comprehensive Survey
Graph Foundation Models: A Comprehensive Survey

Zehong Wang*, Zheyuan Liu*, Tianyi Ma*, Jiazheng Li*, Zheyuan Zhang*, Xingbo Fu*, Yiyang Li*, Zhengqing Yuan*, Wei Song, Yijun Ma, Qingkai Zeng, Xiusi Chen, Jianan Zhao, Jundong Li, Meng Jiang, Pietro Lio, Nitesh Chawla, Chuxu Zhang, Yanfang Ye (* equal contribution, corresponding author)

arXiv preprint 2025 Survey

[Paper] [Repo]

Graph Foundation Models: A Comprehensive Survey

Zehong Wang*, Zheyuan Liu*, Tianyi Ma*, Jiazheng Li*, Zheyuan Zhang*, Xingbo Fu*, Yiyang Li*, Zhengqing Yuan*, Wei Song, Yijun Ma, Qingkai Zeng, Xiusi Chen, Jianan Zhao, Jundong Li, Meng Jiang, Pietro Lio, Nitesh Chawla, Chuxu Zhang, Yanfang Ye (* equal contribution, corresponding author)

arXiv preprint 2025 Survey

[Paper] [Repo]

Training MLPs on Graphs Without Supervision
Training MLPs on Graphs Without Supervision

Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye

ACM International Conference on Web Search and Data Mining (WSDM) 2025

[Paper] [Code]

Training MLPs on Graphs Without Supervision

Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye

ACM International Conference on Web Search and Data Mining (WSDM) 2025

[Paper] [Code]

Can LLMs Convert Graphs to Text-Attributed Graphs?
Can LLMs Convert Graphs to Text-Attributed Graphs?

Zehong Wang, Sidney Liu, Zheyuan Zhang, Tianyi Ma, Chuxu Zhang, Yanfang Ye

Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL) 2025

[Paper] [Code]

Can LLMs Convert Graphs to Text-Attributed Graphs?

Zehong Wang, Sidney Liu, Zheyuan Zhang, Tianyi Ma, Chuxu Zhang, Yanfang Ye

Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL) 2025

[Paper] [Code]

GFT: Graph Foundation Model with Transferable Tree Vocabulary
GFT: Graph Foundation Model with Transferable Tree Vocabulary

Zehong Wang, Zheyuan Zhang, Nitesh Chawla, Chuxu Zhang, Yanfang Ye

Annual Conference on Neural Information Processing Systems (NeurIPS) 2024

[Paper] [Code]

GFT: Graph Foundation Model with Transferable Tree Vocabulary

Zehong Wang, Zheyuan Zhang, Nitesh Chawla, Chuxu Zhang, Yanfang Ye

Annual Conference on Neural Information Processing Systems (NeurIPS) 2024

[Paper] [Code]

Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns
Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns

Zheyuan Zhang*, Zehong Wang*, Shifu Hou, Evan Hall, Landon Bachman, Jasmine White, Vincent Galassi, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye (* equal contribution)

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2024

[Paper] [Code]

Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns

Zheyuan Zhang*, Zehong Wang*, Shifu Hou, Evan Hall, Landon Bachman, Jasmine White, Vincent Galassi, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye (* equal contribution)

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2024

[Paper] [Code]

Subgraph Pooling: Tackling Negative Transfer on Graphs

Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye

International Joint Conference on Artificial Intelligence (IJCAI) 2024

[Paper] [Code]

Subgraph Pooling: Tackling Negative Transfer on Graphs

Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye

International Joint Conference on Artificial Intelligence (IJCAI) 2024

[Paper] [Code]

All publications
Education
  • University of Notre Dame
    University of Notre Dame
    Department of Computer Science and Engineering
    Ph.D. Student
    Aug. 2023 - present
Experience
  • Google
    Google
    Research Intern
    May. 2026 - Aug. 2026
  • Amazon
    Amazon
    Applied Scientist Intern (Part-Time)
    Sept. 2025 - Oct. 2025
  • Amazon
    Amazon
    Applied Scientist Intern
    May. 2025 - Aug. 2025
Services
  • Reviewer, NeurIPS
    2024, 2025, 2026
  • Reviewer, ICLR
    2024, 2025, 2026
  • Reviewer, ICML
    2024, 2025, 2026
  • Reviewer, KDD
    2025, 2026
  • Reviewer, ARR (ACL, EMNLP, NAACL)
    2025, 2026
  • Reviewer, AISTATS
    2025, 2026
  • Reviewer, AAAI
    2024, 2025, 2026
Honors & Awards
  • NSF Access Grant
    2025
  • NeurIPS Scholar Award
    2025
  • ICML Scholar Award
    2025
  • Notre Dame Graduate School Conference Presentation Grant
    2025
  • WSDM Student Travel Award
    2025
  • SDM Doctoral Forum Travel Award
    2024