Author

Yi Nian

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#artificial intelligence Jun 2026

DOG-DPO:Dynamic Optimization in Geometry for Safety Alignment

DOG-DPO is proposed, a training-free data selection framework that treats preference pairs as structured geometric signals and recovers most of the safety gains of full-data training while remaining entirely teacher-free, training-free, and substantially faster than representative selection baselines.

Yi Nian, Tiankai Yang, Yudi Zhang et al. · arXiv.org · 1 citation

Jul 2026

MemoHarness: Agent Harnesses That Learn from Experience

MemoHarness is introduced, an adaptive harness optimization framework that learns from its own executions and improves over the fixed harnesses it is compared against and shows selective transfer to unseen suites and base models.

Yue Huang, Wenjie Wang, Han Bao et al. · arXiv.org · 4 citations