collaborators

5 papers

cs.AI2026

Reasoning Is Not Free: Robust Adaptive Cost-Efficient Routing for LLM-as-a-Judge

Wenbo Zhang, Lijinghua Zhang, Liner Xiang +1

Reasoning-capable large language models (LLMs) have recently been adopted as automated judges, but their benefits and costs in LLM-as-a-Judge settings remain unclear. Through contr…

cs.CL2026

Beyond the Singular: Revealing the Value of Multiple Generations in Benchmark Evaluation

Wenbo Zhang, Hengrui Cai, Wenyu Chen

Large language models (LLMs) have demonstrated significant utility in real-world applications, exhibiting impressive capabilities in natural language processing and understanding.…

cs.AI2026

Supervised Fine-Tuning versus Reinforcement Learning: A Study of Post-Training Methods for Large Language Models

Haitao Jiang, Wenbo Zhang, Jiarui Yao +3

Pre-trained Large Language Model (LLM) exhibits broad capabilities, yet, for specific tasks or domains their attainment of higher accuracy and more reliable reasoning generally dep…

cs.CL2025

Recognizing Limits: Investigating Infeasibility in Large Language Models

Wenbo Zhang, Zihang Xu, Hengrui Cai

Large language models (LLMs) have shown remarkable performance in various tasks but often fail to handle queries that exceed their knowledge and capabilities, leading to incorrect…

stat.ML2025

Where to Intervene: Action Selection in Deep Reinforcement Learning

Wenbo Zhang, Hengrui Cai

Deep reinforcement learning (RL) has gained widespread adoption in recent years but faces significant challenges, particularly in unknown and complex environments. Among these, hig…