Recent pre-trained foundation models provide rich multi-modal priors for downstream 3D vision tasks. However, the effectiveness of these representations in few-shot scenarios is limited by two fundamental challenges: High-dimensional features often contain substantial channel redundancy and task-irrelevant noise, while...
Hang Cheng, Yan Chen, Ming-Yu Fan et al.· 0 citations
Vision2CAD is presented, a visual agent harness that combines vision-language model (VLM) reasoning with deterministic CAD kernel operations and the Geometry Explicit Reference Dataset (GERD), which aligned commands, geometry states and IDs at every modeling step.
Xi Cheng, Chen-Xi Zhai, Hang Cheng et al.· 0 citations
This work introduces Retrieval-Aware Self-Distillation (RASD), which extracts privileged guidance from input-supported facts and evidence distinguishing the positive from hard negatives, and Retrieval-Adaptive Inference (RAI), which learns a retrieval-aware stopping criterion from prefix-level retrieval feedback.
Ming-Zhou Jiang, Pei-Xi Wu, Hang Cheng et al.· 0 citations
WISE (World-model-guided Imagination Scheduling for Efficient Post-training of Vision-Language-Action Models), a unified framework that coordinates when and how world-model imagination is used during policy refinement, is introduced.
Chen-Hao Zhang, Han-Yu Zhao, Hang Cheng et al.· 1 citation
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