李传浩｜清华大学｜学者主页

期刊论文

2026

基于知识增强大模型的杀伤网智能设计方法

秦琳浩，明振军，王国新，阎艳，王武宏，李传浩，丁伟

《兵工学报》

2026

博弈对抗驱动的杀伤网设计策略大空间探索与方案优化

李传浩，明振军，王国新，阎艳，万斯来，陈刚，秦琳浩

《兵工学报》

2026

面向长期演化整体性能提升的复杂装备体系设计空间探索方法

丁伟，明振军，李传浩，王国新，阎艳，陈刚

《兵工学报》

2026

COOPA: A Modular LLM Agent Architecture for Operations Research Problems

Chuanhao Li, Xiao-An Xu, Dirk Bergemann, Ethan X. Fang, Yehua Wei, Zhuoran Yang

arXiv.org

DOI

2025

基于多智能体深度强化学习的无人平台箔条干扰末端防御动态决策方法

李传浩，明振军，王国新，阎艳，丁伟，万斯来，丁涛

《兵工学报》

2025

Provably Efficient Algorithm for Best Scoring Rule Identification in Online Principal-Agent Information Acquisition

Zi-Chen Wang, Chuanhao Li, Hua-Zheng Wang

International Conference on Machine Learning

DOI

2025

Design-Based Bandits Under Network Interference: Trade-Off Between Regret and Statistical Inference

Zi-Chen Wang, Hao-Yang Hong, Chuanhao Li, Haoxuan Li, Zhiheng Zhang, Hua-Zheng Wang

Neural Information Processing Systems

DOI

2025

Build Your Personalized Research Group: A Multiagent Framework for Continual and Interactive Science Automation

Ed Li, Junyu Ren, Xintian Pan, Cat Yan, Chuanhao Li, Dirk Bergemann, Zhuoran Yang

arXiv.org

DOI

2024

支持开放式众包任务优化的强化学习决策方法

李传浩，明振军，王国新，阎艳

《包装工程》

DOI

2024

面向OODA作战流程的防空火力网端对端智能构建算法

罗雨雨，丁伟，明振军，李传浩，王国新，阎艳，王玉茜

《兵工学报》

2024

基于AGE-MOEA的杀伤链建模与优化方法

万斯来，王国新，明振军，李传浩，阎艳，丁伟，袁珂，王玉茜

《兵工学报》

2024

STRIDE: A Tool-Assisted LLM Agent Framework for Strategic and Interactive Decision-Making

Chuanhao Li, Runhan Yang, Tian-Kai Li, Milad Bafarassat, Kourosh Sharifi, Dirk Bergemann, Zhuoran Yang

arXiv.org

DOI

2024

Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?

Fan Yao, Chuanhao Li, Denis Nekipelov, Hong-Ning Wang, Haifeng Xu

International Conference on Machine Learning

DOI

2024

Federated Linear Contextual Bandits with Heterogeneous Clients

Ethan Blaser, Chuanhao Li, Hong-Ning Wang

International Conference on Artificial Intelligence and Statistics

DOI

2024

User Welfare Optimization in Recommender Systems with Competing Content Creators

Fan Yao, Yi-Ming Liao, Mingzhe Wu, Chuanhao Li, Yan Zhu, James Yang, Jing-Zhou Liu, Qifan Wang, Haifeng Xu, Hong-Ning Wang

Knowledge Discovery and Data Mining

DOI

2024

Incentivized Truthful Communication for Federated Bandits

Zhepei Wei, Chuanhao Li, Tian-Ze Ren, Haifeng Xu, Hong-Ning Wang

International Conference on Learning Representations

DOI

2023

How Bad is Top-K Recommendation under Competing Content Creators?

Fan Yao, Chuanhao Li, Denis Nekipelov, Hong-Ning Wang, Haifeng Xu

International Conference on Machine Learning

DOI

2023

Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?

Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu, Qifan Wang, Hong-Ning Wang, Haifeng Xu

Neural Information Processing Systems

DOI

2023

Communication-Efficient Federated Non-Linear Bandit Optimization

Chuanhao Li, Chong Liu, Yu-Xiang Wang

International Conference on Learning Representations

DOI

2023

Pure Exploration in Asynchronous Federated Bandits

Zi-Chen Wang, Chuanhao Li, Chenyu Song, Lianghui Wang, Quanquan Gu, Hua-Zheng Wang

Conference on Uncertainty in Artificial Intelligence

DOI

2023

Incentivized Communication for Federated Bandits

Zhepei Wei, Chuanhao Li, Haifeng Xu, Hong-Ning Wang

Neural Information Processing Systems

DOI

2023

Incentivizing Exploration in Linear Contextual Bandits under Information Gap

Hua-Zheng Wang, Haifeng Xu, Chuanhao Li, Zhiyuan Liu, Hongning Wang

ACM Conference on Recommender Systems

DOI

2023

Learning Kernelized Contextual Bandits in a Distributed and Asynchronous Environment

Chuanhao Li, Huazheng Wang, Mengdi Wang, Hong-Ning Wang

International Conference on Learning Representations

2022

Learning from a Learning User for Optimal Recommendations

Fan Yao, Chuanhao Li, Denis Nekipelov, Hong-Ning Wang, Haifeng Xu

International Conference on Machine Learning

2022

Communication Efficient Federated Learning for Generalized Linear Bandits

Chuanhao Li, Hong-Ning Wang

Neural Information Processing Systems

DOI

2022

Communication Efficient Distributed Learning for Kernelized Contextual Bandits

Chuanhao Li, Hua-Zheng Wang, Mengdi Wang, Hong-Ning Wang

Neural Information Processing Systems

DOI

2021

Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits

Chuanhao Li, Hong-Ning Wang

International Conference on Artificial Intelligence and Statistics

2021

Learning the Optimal Recommendation from Explorative Users

Fan Yao, Chuanhao Li, Denis Nekipelov, Hong-Ning Wang, Haifeng Xu

AAAI Conference on Artificial Intelligence

DOI

2021

When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution

Chuanhao Li, Qingyun Wu, Hong-Ning Wang

Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

DOI

2020

Unifying Clustered and Non-stationary Bandits

Chuanhao Li, Qingyun Wu, Hongning Wang

International Conference on Artificial Intelligence and Statistics

预印本

2026

Training Language Models for Bilateral Trade with Private Information

Dirk Bergemann, Soheil Ghili, Xinyang Hu, Chuanhao Li, Zhuoran Yang

arXiv (Cornell University)

DOI

2026

LLM-Guided Heuristic Design from Simulation Traces: A Case Study in Dynamic Production and AGV Scheduling

Jinbo Li, Chuanhao Li

arXiv preprint

李传浩

精选作品

期刊论文

基于知识增强大模型的杀伤网智能设计方法

博弈对抗驱动的杀伤网设计策略大空间探索与方案优化

面向长期演化整体性能提升的复杂装备体系设计空间探索方法

COOPA: A Modular LLM Agent Architecture for Operations Research Problems

基于多智能体深度强化学习的无人平台箔条干扰末端防御动态决策方法

Provably Efficient Algorithm for Best Scoring Rule Identification in Online Principal-Agent Information Acquisition

Design-Based Bandits Under Network Interference: Trade-Off Between Regret and Statistical Inference

Build Your Personalized Research Group: A Multiagent Framework for Continual and Interactive Science Automation

支持开放式众包任务优化的强化学习决策方法

面向OODA作战流程的防空火力网端对端智能构建算法

基于AGE-MOEA的杀伤链建模与优化方法

STRIDE: A Tool-Assisted LLM Agent Framework for Strategic and Interactive Decision-Making

Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?

Federated Linear Contextual Bandits with Heterogeneous Clients

User Welfare Optimization in Recommender Systems with Competing Content Creators

Incentivized Truthful Communication for Federated Bandits

How Bad is Top-K Recommendation under Competing Content Creators?

Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?

Communication-Efficient Federated Non-Linear Bandit Optimization

Pure Exploration in Asynchronous Federated Bandits

Incentivized Communication for Federated Bandits

Incentivizing Exploration in Linear Contextual Bandits under Information Gap

Learning Kernelized Contextual Bandits in a Distributed and Asynchronous Environment

Learning from a Learning User for Optimal Recommendations

Communication Efficient Federated Learning for Generalized Linear Bandits

Communication Efficient Distributed Learning for Kernelized Contextual Bandits

Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits

Learning the Optimal Recommendation from Explorative Users

When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution

Unifying Clustered and Non-stationary Bandits

预印本

Training Language Models for Bilateral Trade with Private Information

LLM-Guided Heuristic Design from Simulation Traces: A Case Study in Dynamic Production and AGV Scheduling

研究方向