Qirun Zeng

Profile

My background.

I am a Ph.D. candidate in Computer Science at City University of Hong Kong, advised by Prof. Jinhang Zuo. Previously, I worked as a research assistant with Prof. Sibo Wang at the Chinese University of Hong Kong from July to October 2024.

I received my bachelor’s degree in Computer Science and Technology from the School of the Gifted Young at the University of Science and Technology of China, where I was advised by Prof. Xue Chen and Prof. Jinhang Zuo.

Citations
6
h-index
1
i10-index
0
Conference papers
3
Preprints
2

News

Recent research updates.

  1. Our paper WEREWOLF: Reputation-Aware Red-Teaming for Self-Organizing LLM Multi-Agent Systems was accepted to Findings of EMNLP 2026.

  2. Our paper One Rounding Fits All: Memory-Efficient Approximation Algorithms for Partition-Constrained Influence Maximization was accepted to KDD 2026.

  3. Our paper Fusing Reward and Dueling Feedback in Stochastic Bandits was accepted to ICML 2025.

View all news

Research Focus

I study sequential decision-making under limited, noisy, or hybrid feedback. My current work focuses on bandit learning and influence maximization.

  • Learning Theory
  • Influence Maximization
  • Game Theory
  • Multi-Agent Systems

10-second Bandit

Can you identify the better arm before your rounds run out?

Explore or exploit?

Two arms hide different reward probabilities. Learn which one is better before your rounds run out.

Round 0 / 10
Reward 0
Expected regret hidden
Reward trail

    This is the exploration–exploitation dilemma in miniature. See how I study bandit feedback

    Selected Publications

    * Equal contribution.† Mentored student.

    WEREWOLF: Reputation-Aware Red-Teaming for Self-Organizing LLM Multi-Agent Systems

    Manhin Poon†, Qirun Zeng, Xiangxiang Dai, Jinhang Zuo

    In Findings of the Association for Computational Linguistics: EMNLP 2026

    EMNLP'2026

    One Rounding Fits All: Memory-Efficient Approximation Algorithms for Partition-Constrained Influence Maximization

    Qixin Zhang*, Qirun Zeng*, Hui Lu, Pingchuan Ma, Jinhang Zuo, Renqiang Luo, Yi Yu, Dacheng Tao

    In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining

    KDD'2026 Code

    Fusing Reward and Dueling Feedback in Stochastic Bandits

    Xuchuang Wang, Qirun Zeng, Jinhang Zuo, Xutong Liu, Mohammad Hajiesmaili, John C. S. Lui, Adam Wierman

    In Proceedings of the 42nd International Conference on Machine Learning

    ICML'2025 Code

    View all publications

    Service

    Academic reviewing and service.

    2026

    Reviewer

    ICLR and NeurIPS.

    2025

    Reviewer

    ICML and NeurIPS.

    Teaching

    I have served as a teaching assistant for programming, data structures, algorithms, and mathematical analysis courses.

    View teaching experience