Xiangmou Qu

Orcid: 0009-0006-4449-522X

According to our database1, Xiangmou Qu authored at least 13 papers between 2024 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
TopoClaw: A Human-Centric and Topology-Aware Agent Operating System.
CoRR, May, 2026

From Transfer to Collaboration: A Federated Framework for Cross-Market Sequential Recommendation.
CoRR, April, 2026

ColorBench: Benchmarking Mobile Agents with Graph-Structured Framework for Complex Long-Horizon Tasks.
Proceedings of the ACM Web Conference 2026, 2026

2025
JCSRC: Joint Client Selection and Resource Configuration for Energy-Efficient Multi-Task Federated Learning.
IEEE Trans. Computers, December, 2025

ColorAgent: Building A Robust, Personalized, and Interactive OS Agent.
CoRR, October, 2025

ColorBench: Benchmarking Mobile Agents with Graph-Structured Framework for Complex Long-Horizon Tasks.
CoRR, October, 2025

VeriOS: Query-Driven Proactive Human-Agent-GUI Interaction for Trustworthy OS Agents.
CoRR, September, 2025

MobileUse: A GUI Agent with Hierarchical Reflection for Autonomous Mobile Operation.
CoRR, July, 2025

FedEcover: Fast and Stable Converging Model-Heterogeneous Federated Learning with Efficient-Coverage Submodel Extraction.
Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

OLearning: A Geo-Distributed System for Device-Cloud Collaborative Computing.
Proceedings of the Database Systems for Advanced Applications, 2025

Personalized Federated Recommendation with Multi-Faceted User Representation and Global Consistent Prototype.
Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

FedSA: A Unified Representation Learning via Semantic Anchors for Prototype-based Federated Learning.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024
Voltran: Unlocking Trust and Confidentiality in Decentralized Federated Learning Aggregation.
IEEE Trans. Inf. Forensics Secur., 2024


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