3 papers
eess.SP2026
Clustering-Based User Selection in Federated Learning: Metadata Exploitation for 3GPP Networks
Ce Zheng, Shiyao Ma, Ke Zhang +2
Federated learning (FL) enables collaborative model training without sharing raw user data, but conventional simulations often rely on unrealistic data partitioning and current use…
eess.SP2026
Fast Collaborative Inference via Distributed Speculative Decoding
Ce Zheng, Ke Zhang, Chen Sun +3
Speculative decoding accelerates large language model (LLM) inference by allowing a small draft model to predict multiple future tokens for verification by a larger target model. I…
cs.MA2025
Tool-RoCo: An Agent-as-Tool Self-organization Large Language Model Benchmark in Multi-robot Cooperation
Ke Zhang, Xiaoning Zhao, Ce Zheng +5
This study proposes Tool-RoCo, a novel benchmark for evaluating large language models (LLMs) in long-term multi-agent cooperation based on RoCo, a multi-robot cooperative benchmark…