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Author

Chunyu Yang

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Preprint Aug 2026

Learning from Consensus and Disagreement: Unsupervised On-Policy Self-Distillation with Minority-Trajectory Contrast

CoDA is introduced, a fully unsupervised framework that creates reliable privileged information entirely from the latent uncertainty structure of a model's own unlabeled rollouts and provides robust regularization without requiring the strong assumption that the consensus is the absolute ground truth.

Jiaxin Guo, Yanwei Yue, Xuanbo Fan et al. · 0 citations
Conference Open access 2026

COSMOS: Connectivity-Oriented Submodular Maximization for Optimal Subgraph Retrieval

This paper proposes COS-MOS, a unified framework that formalizes evidence retrieval as a constrained submodular maximization problem, and introduces Structure-Aware Contrastive Tuning to align semantic space with KG topology.

Boci Peng, Xiao Liu, Bo-Ren Hu et al. · 0 citations

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