arXiv AI By Zekai Jin, Hanrong Zhang, Yihong Tang, Fei Hu, Zhen Dong, Yi Shao

Not All Agreement Counts as Corroboration: Provenance-Conserving Multi-View Fusion for Typed Action Admission in Human-Robot Collaboration

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The paper introduces PACT, a provenance‑conserving fusion method for typed action admission in human‑robot collaboration. PACT treats evidence countability as a relational variable, using a supplied provenance partition to define countable units and accumulating support only across these units. Experiments on 31,200 evaluations in 48 scene clusters show that PACT achieves a lower normalized risk‑coverage area than singleton aggregation, and in offline human‑robot collaboration it admits 47 of 57 reference‑consistent candidates without any reference‑inconsistent admissions.

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arXiv AI
Jul 29

CoTinyVLA: Chain-of-Thought Distillation for a Sub-Billion-Parameter Vision-Language-Action Model

arXiv:2607. 25487v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models translate natural-language commands into robot action sequences, but leading systems on the LIBERO-Plus robustness benchmark use three- to seven-billion-parameter backbones whose memory demands can exceed embedded robotic budgets.

By Minhyeok Lee, Chiyoung Kim, Chanhoe Gu, Seongrok Kim, Sanghyuk Roy Choi, Donghwan Hwang, Donghun Ryu, Seokhyun Kim