13 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…