Author

Yutao Mou

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Preprint Aug 2026

Mitigating Rubric Interference in LLM Judges via On-Policy Self-Distillation

LLM judges increasingly evaluate responses against fine-grained rubric checklists. When a sample requires multiple rubrics, current methods typically assess each in a separate inference call. Evaluating all rubrics in a single pass is a natural alternative with greater efficiency, but we find that it introduces rubric...

Dingyao Yu, Tong Zhang, Yutao Mou et al. · 0 citations

#artificial intelligence Preprint Sep 2026

FLARE: A Full-Lifecycle Dense Supervision Paradigm for Long-Horizon Coding Agents via Generative Reward Model

While test-time scaling enhances Large Language Model (LLM) agents in long-horizon software engineering (SWE), sparse binary rewards (Pass/Fail) create a severe credit assignment crisis and waste failed exploratory trajectories. Current trajectory optimization and scaling methods are costly and structurally limited, re...

Jing-Xuan Xu, Gang Wu, Ya-Nan Wu et al. · 0 citations

Preprint Aug 2026

ToolHazard: Scaling Adversarial Environments for Security Evaluation and Alignment of LLM-based Agents

Experiments reveal substantial agent vulnerabilities and show that injection timing and placement affect attack effectiveness, and ToolHazard-generated alignment data improves security on both ToolHazard-Bench and AgentDojo while preserving benign task utility.

Yutao Mou, Pengfei Yang, Zhenfei Yin et al. · 2 citations