5 papers
Adaptive Power Sampling for LLM Reasoning
Bingnan Xiao, Chenhao Yang, Bingcong Li +2
Sequence-level power sampling has recently emerged as a training-free approach to reasoning by sampling from a sharpened output distribution of a base large language model (LLM). N…
Goodput Maximization for Large Language Model Edge Inference: A Two-Phase Maskable PPO Approach
Xiaojing Chen, Qi Zhang, Wei Ni +2
This paper presents a novel two-phase maskable proximal policy optimization (TP-MPPO) algorithm, which maximizes the system goodput counting request throughput with strict service…
Agentic AI for Bilevel Long-Term Optimization of Policy-Driven Physical Layer Systems
Bingnan Xiao, Chenhao Yang, Wei Ni +2
Network operators' changing policies, service requirements, and stringent real-time constraints render existing methods designed with fixed objectives and constraints ineffective.…
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…
Networking-Aware Energy Efficiency in Agentic AI Inference: A Survey
Xiaojing Chen, Haiqi Yu, Wei Ni +5
The rapid emergence of Large Language Models (LLMs) has catalyzed Agentic artificial intelligence (AI), autonomous systems integrating perception, reasoning, and action into closed…