16 papers
Explainable AI for Next-Generation Wireless Physical Layer: Basics, State-of-the-Art, and Open Challenges
Bingnan Xiao, Shuyan Hu, Xiaojing Chen +5
Next-generation wireless systems are expected to be ``AI-native," with neural networks (NNs) embedded throughout the physical (PHY) layer protocol stack to improve spectral efficie…
Selective Rollout: Mid-Trajectory Termination for Multi-Sample Agent RL
Zhiyuan Zhai, Xin Wang
Group-relative RL training (GRPO) samples a small group of parallel rollouts for every training prompt and uses their within-group reward spread to compute per-trajectory advantage…
Revisable by Design: A Theory of Streaming LLM Agent Execution
Zhiyuan Zhai, Ming Li, Xin Wang
Current LLM agents operate under an implicit but universal assumption: execution is a transaction -- the user submits a request, the agent works in isolation, and only upon complet…
How Much Thinking is Enough? Quantifying and Understanding Redundancy in LLM Reasoning
Zhiyuan Zhai, Xinkai You, Wenjing Yan +1
Reasoning-capable large language models solve hard problems by emitting long chains of thought, paying heavily in latency, GPU time, and energy. Casual inspection of their traces r…
Does RL Expand the Capability Boundary of LLM Agents? A PASS@(k,T) Analysis
Zhiyuan Zhai, Wenjing Yan, Xiaodan Shao +1
Does reinforcement learning genuinely expand what LLM agents can do, or merely make them more reliable? For static reasoning, recent work answers the second: base and RL pass@k cur…
Adaptive Test-Time Compute Allocation for Reasoning LLMs via Constrained Policy Optimization
Zhiyuan Zhai, Bingcong Li, Bingnan Xiao +2
Test-time compute scaling, the practice of spending extra computation during inference via repeated sampling, search, or extended reasoning, has become a powerful lever for improvi…
Evidential Quantum Vertical Federated Learning
Hao Luo, Zhiyuan Zhai, Qianli Zhou +3
Quantum federated learning (QFL) has recently emerged as a promising paradigm for privacy-preserving collaborative learning, yet most existing studies focus on horizontal federated…
Event-Triggered Gossip for Distributed Learning
Zhiyuan Zhai, Xiaojun Yuan, Wei Ni +3
While distributed learning offers a new learning paradigm for distributed network with no central coordination, it is constrained by communication bottleneck between nodes. We deve…
Trajectory Design for UAV-Assisted Logistics Collection in Low-Altitude Economy
Zhiyuan Zhai, Yuan Gao, Wei Ni +2
Low-altitude economy (LAE) is rapidly emerging as a key driver of innovation, encompassing economic activities taking place in airspace below 500 meters. Unmanned aerial vehicles (…
Learning Performance Optimization for Edge AI System with Time and Energy Constraints
Zhiyuan Zhai, Wei Ni, Xin Wang
Edge AI, which brings artificial intelligence to the edge of the network for real-time processing and decision-making, has emerged as a transformative technology across various app…
Spectral-Convergent Decentralized Machine Learning: Theory and Application in Space Networks
Zhiyuan Zhai, Shuyan Hu, Wei Ni +2
Decentralized machine learning (DML) supports collaborative training in large-scale networks with no central server. It is sensitive to the quality and reliability of inter-device…
Decentralized Federated Learning with Distributed Aggregation Weight Optimization
Zhiyuan Zhai, Xiaojun Yuan, Xin Wang +1
Decentralized federated learning (DFL) is an emerging paradigm to enable edge devices collaboratively training a learning model using a device-to-device (D2D) communication manner…
Integrated Sensing and Communication with UAV Swarms via Decentralized Consensus ADMM
Zhiyuan Zhai, Wei Ni, Xin Wang +2
UAV swarms can form virtual antenna arrays to exploit additional spatial degrees of freedom and enhance integrated sensing and communication (ISAC). The optimization of UAV positio…
UAV-Enabled Asynchronous Federated Learning
Zhiyuan Zhai, Xiaojun Yuan, Xin Wang +1
To exploit unprecedented data generation in mobile edge networks, federated learning (FL) has emerged as a promising alternative to the conventional centralized machine learning (M…
Decentralized Federated Learning via MIMO Over-the-Air Computation: Consensus Analysis and Performance Optimization
Zhiyuan Zhai, Xiaojun Yuan, Xin Wang
Decentralized federated learning (DFL), inherited from distributed optimization, is an emerging paradigm to leverage the explosively growing data from wireless devices in a fully d…
Energy-Efficient UAV-Mounted RIS Assisted Mobile Edge Computing
Zhiyuan Zhai, Xinhong Dai, Bin Duo +2
Unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS) have been recently applied in the field of mobile edge computing (MEC) to improve the data exchange envir…