Zekun Li

Zekun Li 李泽坤

Research Scientist, Google DeepMind 算法研究员，Google DeepMind
I work on Gemini post-training on tool use. I got my Ph.D. from UC Santa Barbara in 2025, advised by William Wang and Xifeng Yan. My research focuses on building controllable, robust, and reliable LLM agents. I am also passionate about AI for Science, with an emphasis on applying AI to healthcare and materials science.
我从事 Gemini 工具使用的后训练研究。 2025 年获加州大学圣塔芭芭拉分校计算机科学博士学位，导师为 William Wang 和 Xifeng Yan。 主要研究方向为可控、鲁棒和可靠的大语言模型智能体。 同时致力于 AI for Science，重点关注 AI 在医疗健康和材料科学领域的应用。

Highlights 亮点

Publications 发表论文

h-index: 21 · 2,300+ citations · Google Scholar
Dongsen Zhang, Zekun Li, Xu Luo, Xuannan Liu, Pei Pei Li, Wenjun Xu. "MCP Security Bench (MSB): Benchmarking Attacks Against Model Context Protocol in LLM Agents" ICLR 2026
Xuannan Liu*, Zekun Li*, et al. "Video-SafetyBench: A Benchmark for Safety Evaluation of Video LVLMs" NeurIPS 2025 DB
Yexiang Liu, Zekun Li, Zhi Fang, Nan Xu, Ran He, Tieniu Tan. "Rethinking the Role of Prompting Strategies in LLM Test-Time Scaling" ACL 2025 ACL Outstanding Paper (26/8000)
Zekun Li, Baolin Peng, Pengcheng He, Xifeng Yan. "Evaluating the Instruction-Following Robustness of Large Language Models to Prompt Injection" EMNLP 2024 Main
Zekun Li, Zhiyu Chen, Mike Ross, et al. "Large Language Models as Zero-shot Dialogue State Tracker through Function Calling" ACL 2024 Main
Zekun Li, Baolin Peng, Pengcheng He, Michel Galley, Jianfeng Gao, Xifeng Yan. "Guiding Large Language Models via Directional Stimulus Prompting" NeurIPS 2023
Forbes | Wikipedia | Prompting Guide
Zekun Li, Shiyang Li, Xifeng Yan. "Time Series as Images: Vision Transformer for Irregularly Sampled Time Series" NeurIPS 2023
Zekun Li, Wenhu Chen, Shiyang Li, Hong Wang, Jing Qian, Xifeng Yan. "Controllable Dialogue Simulation with In-Context Learning" EMNLP 2022 Findings
Zekun Li*, Zeyu Cui*, Shu Wu, Xiaoyu Zhang, Liang Wang. "Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction" CIKM 2019
2026
Dongsen Zhang, Zekun Li, Xu Luo, Xuannan Liu, Pei Pei Li, Wenjun Xu. "MCP Security Bench (MSB): Benchmarking Attacks Against Model Context Protocol in LLM Agents" ICLR 2026
Yuheng Tang, Kaijie Zhu, ..., Zekun Li, et al. "DevOps-Gym: Benchmarking AI Agents in Software DevOps Cycle" ICLR 2026
Xing Cui, Yueying Zou, Zekun Li, et al. "T2 Agent: A Tool-augmented Multimodal Misinformation Detection Agent with MCTS" AAAI 2026 (Oral)
Canyu Chen*, Baixiang Huang*, Zekun Li, et al. "Can Editing LLMs Inject Harm?" AAAI 2026
2025
Xuannan Liu*, Zekun Li*, et al. "Video-SafetyBench: A Benchmark for Safety Evaluation of Video LVLMs" NeurIPS 2025 DB
Chenghanyu Zhang*, Zekun Li*, et al. "SpineBench: Benchmarking Multimodal LLMs for Spinal Pathology Analysis" ACM Multimedia DB, 2025
Yexiang Liu, Zekun Li, Zhi Fang, Nan Xu, Ran He, Tieniu Tan. "Rethinking the Role of Prompting Strategies in LLM Test-Time Scaling" ACL, 2025 ACL Outstanding Paper (26/8000)
Yexiang Liu, Jie Cao, Zekun Li, Ran He, Tieniu Tan. "Breaking Mental Set to Improve Reasoning through Diverse Multi-Agent Debate" ICLR 2025
Xuannan Liu, Zekun Li, et al. "MMFakeBench: A Mixed-Source Multimodal Misinformation Detection Benchmark for LVLMs" ICLR 2025
Zekun Li, Xianjun Yang, et al. "MMSci: A Multimodal Multi-Discipline Dataset for PhD-Level Scientific Comprehension" AI4MAT@ICLR 2025 (Spotlights)
Xinlu Zhang, Chenxin Tian, Xianjun Yang, Licahng Chen, Zekun Li, Linda Ruth Petzold. "AlpaCare: Instruction-tuned Large Language Models for Medical Application" SciFM@ICLR 2025
2024
Zekun Li, Baolin Peng, Pengcheng He, Xifeng Yan. "Evaluating the Instruction-Following Robustness of Large Language Models to Prompt Injection" EMNLP 2024 Main
Xing Cui, Peipei Li, Zekun Li, Xuannan Liu, Yueying Zou, Zhaofeng He. "Localize, Understand, Collaborate: Semantic-Aware Dragging via Intention Reasoner" NeurIPS 2024
Zekun Li, Zhiyu Chen, Mike Ross, et al. "Large Language Models as Zero-shot Dialogue State Tracker through Function Calling" ACL 2024 Main
Xuannan Liu, Peipei Li, Huaibo Huang, Zekun Li, et al. "FKA-Owl: Advancing Multimodal Fake News Detection through Knowledge-Augmented LVLM" ACM Multimedia 2024
Xing Cui, Zekun Li, Peipei Li, Huaibo Huang, Zhaofeng He. "InstaStyle: Inversion Noise of a Stylized Image is Secretly a Style Adviser" ECCV 2024
Shiyang Li, Jianshu Chen, et al., Zekun Li, et al. "Explanations from Large Language Models Make Small Reasoners Better" SAI@AAAI 2024
2023
Zekun Li, Baolin Peng, Pengcheng He, Michel Galley, Jianfeng Gao, Xifeng Yan. "Guiding Large Language Models via Directional Stimulus Prompting" NeurIPS 2023
Forbes | Wikipedia | Prompting Guide
Zekun Li, Shiyang Li, Xifeng Yan. "Time Series as Images: Vision Transformer for Irregularly Sampled Time Series" NeurIPS 2023
Xing Cui*, Zekun Li*, Peipei Li, Yibo Hu, Hailin Shi, Zhaofeng He. "ChatEdit: Towards Multi-turn Interactive Facial Image Editing via Dialogue" EMNLP 2023 Main
Jing Qian*, Hong Wang*, Zekun Li, Shiyang Li, Xifeng Yan. "Limitations of Language Models in Arithmetic and Symbolic Induction" ACL 2023 Main
2022 & Earlier
Zekun Li, Wenhu Chen, Shiyang Li, Hong Wang, Jing Qian, Xifeng Yan. "Controllable Dialogue Simulation with In-Context Learning" EMNLP 2022 Findings
Zekun Li*, Hong Wang*, et al. "Making Something out of Nothing: Building Robust Task-oriented Dialogue Systems from Scratch" 1st Proceedings of Alexa Prize TaskBot (2021)
Zeyu Cui*, Zekun Li*, Shu Wu, Xiaoyu Zhang, Qiang Liu, Liang Wang, Mengmeng Ai. "DyGCN: Dynamic Graph Embedding with Graph Convolutional Network" IEEE TNNLS 2022
Yujia Zheng, Siyi Liu, Zekun Li, Shu Wu. "Cold-start Sequential Recommendation via Meta Learner" AAAI 2021
Yujia Zheng, Siyi Liu, Zekun Li, Shu Wu. "DGTN: Dual-channel Graph Transition Network for Session-based Recommendation" NeuRec@ICDM 2020
Zekun Li*, Zeyu Cui*, Shu Wu, Xiaoyu Zhang, Liang Wang. "Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction" CIKM 2019
Zekun Li*, Zeyu Cui*, Shu Wu, Xiaoyu Zhang, Liang Wang. "Semi-supervised Compatibility Learning across Categories for Clothing Matching" ICME 2019
Zeyu Cui*, Zekun Li*, Shu Wu, Xiaoyu Zhang, Liang Wang. "Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networks" WWW 2019
Xuemeng Song, Fuli Feng, Jinhuan Liu, Zekun Li, Liqiang Nie, Jun Ma. "NeuroStylist: Neural Compatibility Modeling for Clothing Matching" ACM Multimedia 2017

Talks 学术报告

MMSci: A Multimodal Multi-Discipline Dataset for PhD-Level Scientific Comprehension MMSci: 用于研究生级多学科多模态科学理解的数据集 — POSCO Holdings, 2024
Controllable LLM-based Intelligent Assistants 可控的基于大语言模型的智能助手 — UT Dallas, 2024
Guiding LLMs via Directional Stimulus Prompting 通过方向性刺激提示引导大型语言模型 — Walmart / Tencent AI Lab / Microsoft Azure AI, 2023
Building Robust Task-oriented Dialogue Systems from Scratch 从零开始构建鲁棒的任务导向对话系统 — Amazon Alexa AI, 2022

Service 学术服务

Reviewer: ICML, AISTATS, NeurIPS, ICLR, AAAI, ACL ARR, COLING, EMNLP, WWW, IEEE TNNLS, TKDE 审稿人：ICML, AISTATS, NeurIPS, ICLR, AAAI, ACL ARR, COLING, EMNLP, WWW, IEEE TNNLS, TKDE