الباحثون

Xiangcheng Zhan

المنشورات 2

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ROT: Rotating Hidden States towards Contextual Vectors for Hallucination Mitigation in LVLMs

Large Vision-Language Models (LVLMs) frequently suffer from object hallucination. Existing training-free interventions primarily manipulate attention weights, which indirectly affect the deep semantics reaching the final predictive layers. In this work, we shift our focus to the hidden state vectors extracted after sel …

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Direct Experience World-Model Optimization: Learning the World Beyond Action Imitation

Xiangcheng Zhan, Zirui Chen, Yicheng Zhao وآخرون · 2026

World-Action Models (WAMs) couple action generation with predictions of how physical interactions unfold. However, current post-deployment learning paradigms typically improve behavior without requiring better world predictions. Especially in dexterous manipulation, small execution errors can compound in high-dimension …

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