Author

Kun-Wang Zheng

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Jul 2026

SERPO: Self-Evolving Rubric Policy Optimization for Open-Ended Test-Time Reinforcement Learning

SERTPO (Self-Evolving Rubric Policy Optimization), which replaces answer voting with a closed loop that co-evolves response evidence, query-specific rubrics, and policy parameters, and supports OOD transfer and continued cross-benchmark evolution.

Jian-Ze Wang, Kun-Wang Zheng, Ying Liu et al. · arXiv.org · 2 citations

#artificial intelligence Preprint Sep 2026

Everything in Moderation: Per-Domain Coverage Optima and Alignment-Resistant Domain Gaps in Multi-Domain Mid-Training

Mid-training, the stage between pre-training and alignment, is where a model's per-domain data composition is typically set by data availability rather than principled design. We ask what that decision buys, and whether a later alignment pass can undo it. In a controlled logical-reasoning setting (Qwen3-8B-Base, with a...

Yun-Peng Xu, Kun-Wang Zheng · 0 citations