Publications

(*equal contribution, #corresponding author, listed in chronological order)

Preprints

• [arXiv] HiLoRA: Adaptive Hierarchical LoRA Routing for Training-Free Domain Generalization
  Ziyi Han, Huanyu Wang, Zeyu Zhang, Xiangxiang Dai, Xutong Liu, John C.S. Lui.
  

Conferences:

• [WWW] BANCO: Drift-Aware Batched Bandits for Adaptive Proximity Graph Pruning
  Jin Cheng, Xiangxiang Dai, Ning Ning Ding, John C.S. Lui, Jian Wei Huang.
  Accepted in the ACM The Web Conference (WWW), 2026.
  

• [INFOCOM] Constraint-Aware Combinatorial Bandits: Theoretical Foundations and Network Applications
  Xiangxiang Dai, Jin Li, Xutong Liu, Anqi Yu, John C.S. Lui.
  Accepted in the IEEE International Conference on Computer Communications (INFOCOM), 2026.
  [arXiv]

• [INFOCOM] Semantic Caching for Low-Cost LLM Serving: From Offline Learning to Online Adaptation
  Xutong Liu, Baran Atalar, Xiangxiang Dai#, Jinhang Zuo, Siwei Wang, John C.S. Lui, Wei Chen, Carlee Joe-Wong.
  Accepted in the IEEE International Conference on Computer Communications (INFOCOM), 2026.
  [arXiv]

• [INFOCOM] BEVCooper: Accurate and Communication-Efficient Bird’s-Eye-View Perception in Vehicular Networks
  Jiawei Hou, Peng Yang, Xiangxiang Dai, Mingliu Liu, Conghao Zhou.
  Accepted in the IEEE International Conference on Computer Communications (INFOCOM), 2026.
  

• [INFOCOM] Faster, Smaller, and Smarter: Task-Aware Expert Merging for Online MoE Inference
  Ziyi Han, Xutong Liu, Ruiting Zhou, Xiangxiang Dai, John C.S. Lui.
  Accepted in the IEEE International Conference on Computer Communications (INFOCOM), 2026.
  [arXiv]

• [AAAI] A Multi-Agent Conversational Bandit Approach to Online Evaluation and Selection of User-Aligned LLM Responses
  Xiangxiang Dai, Yuejin Xie, Maoli Liu, Xuchuang Wang, Zhuohua Li, Huanyu Wang, John C.S. Lui.
  Accepted in the Annual AAAI Conference on Artificial Intelligence (AAAI), 2026.
  [arXiv], [Code], [Poster]

• [AAAI] Online Multi-LLM Selection via Contextual Bandits under Unstructured Context Evolution
  Manhin Poon, Xiangxiang Dai, Xutong Liu, Fang Kong, John C.S. Lui, Jinhang Zuo.
  Accepted in the Annual AAAI Conference on Artificial Intelligence (AAAI), 2026.
  [arXiv], [Code]

• [ICDE] Trading Vector Data in Vector Databases
  Jin Cheng, Xiangxiang Dai, Ning Ning Ding, John C.S. Lui, Jian Wei Huang.
  Accepted in the IEEE International Conference on Data Engineering (ICDE) 2026.
  [arXiv]

• [SIGKDD] A Unified Online-Offline Framework for Co-Branding Campaign Recommendations
  Xiangxiang Dai, Xiaowei Sun, Jinhang Zuo, Xutong Liu, John C.S. Lui.
  Accepted in the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025.
  [Link], [arXiv], [Code], [Promotional Video], [Slides]
  

• [SIGKDD] Leveraging the Power of Conversations: Optimal Key Term Selection in Conversational Contextual Bandits
  Maoli Liu, Zhuohua Li, Xiangxiang Dai, John C.S. Lui.
  Accepted in the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025. (AR: 365/1988=18.4%)
  [Link], [arXiv]

• [SIGMETRICS] Combinatorial Logistic Bandits
  Xutong Liu, Xiangxiang Dai, Xuchuang Wang, Mohammad Hajiesmaili, John C.S. Lui.
  Accepted in the ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), 2025.
  🏆Best Paper Finalists (Top 5)
  [Link], [arXiv], [Code], [Slides]

• [ICML] Offline Learning for Combinatorial Multi-armed Bandits
  Xutong Liu, Xiangxiang Dai#, Jinhang Zuo#, Siwei Wang, Carlee-Joe Wong, John C.S. Lui, Wei Chen#.
  Accepted in the International Conference on Machine Learning (ICML), 2025.
  [Link], [arXiv], [Slides]

• [ICLR] Demystifying Online Clustering of Bandits: Enhanced Exploration Under Stochastic and Smoothed Adversarial Contexts
  Zhuohua Li, Maoli Liu, Xiangxiang Dai, John C.S. Lui.
  Accepted in the International Conference on Learning Representations (ICLR), 2025.
  [OpenReview], [Poster], [arXiv]

• [WWW] Towards Efficient Conversational Recommendations: Expected Value of Information Meets Bandit Learning
  Zhuohua Li, Maoli Liu, Xiangxiang Dai, John C.S. Lui.
  Accepted in the ACM The Web Conference (WWW), 2025.
  [Link], [Poster]

• [ACM MM] AxiomVision: Accuracy-Guaranteed Adaptive Visual Model Selection for Perspective-Aware Video Analytics
  Xiangxiang Dai, Zeyu Zhang, Peng Yang, Yuedong Xu, Xutong Liu, John C.S. Lui.
  Accepted in the ACM Multimedia (MM), 2024.
  [Link], [arXiv], [Poster], [Code], [ACM showcase on Kudos]
  

• [IWQoS] Quantifying the Merits of Network-Assist Online Learning in Optimizing Network Protocols
  Xiangxiang Dai*, Zhiyong Wang*, Jiancheng Ye, and John C.S. Lui.
  Accepted in the IEEE/ACM International Symposium on Quality of Service (IWQoS), 2024.
  [Link], [PDF], [Slides]
  

Journals:

• [AIJ] Exploring Multi-Layered Networks through Random Walks: Bridging Offline Optimization and Online Learning
  Xiangxiang Dai, Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C.S. Lui.
  Accepted by Elsevier Artificial Intelligence Journal (AIJ), 2026.
  

• [TON] Combinatorial Logistic Online Learning and Its Applications in Nonlinear Networked Systems
  Xutong Liu, Xiangxiang Dai#, Xuchuang Wang#, Carlee Joe-Wong, Mohammad Hajiesmaili, John C.S. Lui.
  Aceecpted by IEEE/ACM Transactions on Networking (TON), 2026.
  

• [TCCN] Networked Edge Resource Orchestration for Mobile AI-Generated Content Services
  Yuxin Liang, Peng Yang, Xiangxiang Dai, Yuanyuan He, Feng Lyu.
  Published in the IEEE Transactions on Cognitive Communications and Networking (TCCN), 2026.
  

• [TON] Variance-Aware Bandit Framework for Dynamic Probabilistic Maximum Coverage Problem with Triggered or Self-Reliant Arms
  Xiangxiang Dai, Xutong Liu, Jinhang Zuo, Hong Xie, Carlee Joe-Wong, John C.S. Lui.
  Accepted in the IEEE/ACM Transactions on Networking (TON), 2025.
  [Link]

• [T-ITS] Enhancing Cooperative LiDAR-based Perception Accuracy in Vehicular Edge Networks
  Jiawei Hou, Peng Yang, Xiangxiang Dai, Tian Qin, Feng Lyu.
  Accepted in the IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2025.
  [Link]

• [TKDE] Conversational Recommendation with Online Learning and Clustering on Misspecified Users
  Xiangxiang Dai*, Zhiyong Wang*, Jize Xie, Xutong Liu, John C.S. Lui.
  Accepted in the IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.
  [Link]

• [TKDE] Online Learning and Detecting Corrupted Users for Conversational Recommendation Systems
  Xiangxiang Dai*, Zhiyong Wang*, Jize Xie, Tong Yu, and John C.S. Lui.
  Accepted in the IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.
  [Link]

• [TII] RESPIRE: Reducing Spatial–Temporal Redundancy for Efficient Edge-Based Industrial Video Analytics
  Xiangxiang Dai, Peng Yang, Xinyu Zhang, Zhewei Dai, and Li Yu.
  Accepted in the IEEE Transactions on Industrial Informatics (TII), 2022.
  [Link]