publications

2026

  1. Major Revision
    Dynamic Balancing and Matchmaking in Competitive Live-Service Games
    Jialin Li, Zihao Qu, and Mengfan Xu
    Major Revision at Management Science (MS), 2026

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  2. AISTATS
    Open Multi-agent Multi-armed Bandit with Applications in Permissionless Blockchain.
    Mengfan Xu, and Diego Klabjan
    International Conference on Artificial Intelligence and Statistics (AISTATS), 2026

  3. AISTATS
    MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation
    Wei Shen, Yaxiang Zhang, Minhui Huang, Mengfan Xu, Jiawei Zhang, and Cong Shen
    International Conference on Artificial Intelligence and Statistics (AISTATS), 2026

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  4. ACM SIGMETRICS
    Heterogeneous Multi-agent Multi-armed Bandits on Stochastic Block Models
    Mengfan Xu, Liren Shan, Fatemeh Ghaffari, Xuchuang Wang, Xutong Liu, and Mohammad Hajiesmaili
    Proceedings of the ACM on Measurement and Analysis of Computer Systems (ACM SIGMETRICS/POMACS), 2026

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2025

  1. NeurIPS
    Distributed Multi-agent Bandits Over Erdős-Rényi Random Networks
    Jingyuan Liu, Hao Qiu, Lin Yang, and Mengfan Xu
    Advances on Neural Information Processing Systems (NeurIPS), 2025

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  2. AISTATS
    Multi-agent Multi-armed Bandit Regret Complexity and Optimality
    Mengfan Xu, and Diego Klabjan
    International Conference on Artificial Intelligence and Statistics (AISTATS), 2025

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  3. WSC
    Multi-agent Multi-armed Bandit with Fully Heavy-tailed Dynamics
    Xingyu Wang, and Mengfan Xu
    Winter Simulation Conference (WSC), 2025

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2024

  1. RLC Workshop
    Decentralized Blockchain-based Robust Multi-agent Multi-armed Bandit
    Mengfan Xu, and Diego Klabjan
    RLC Workshop on Coordination and Cooperation in Multi-Agent Reinforcement Learning (CoCoMARL), 2024

    Honorable Mention

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2023

  1. NeurIPS
    Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards
    Mengfan Xu, and Diego Klabjan
    Advances on Neural Information Processing Systems (NeurIPS), 2023

    Spotlight

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  2. ICML
    Pareto Regret Analyses in Multi-objective Multi-armed Bandit
    Mengfan Xu, and Diego Klabjan
    International Conference on Machine Learning (ICML), 2023

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2022

  1. KDD
    Gcf: Generalized causal forest for heterogeneous treatment effect estimation in online marketplace
    Shu Wan, Chen Zheng, Zhonggen Sun, Mengfan Xu, Xiaoqing Yang, Hongtu Zhu, and Jiecheng Guo
    In KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond, 2022

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