cs.RO · 2026-08-12 · No. 82

Robotics, 2026-08-12.

3 new papers in cs.RO. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

3 entries
  1. 01

    Surgical WAM: A World-Action Model for Data-Efficient Surgical Robot Learning

    Wenrui Bao, Tianyun Jiang, Zhiben Chen, Ser-Nam Lim, Peter D. Peng, Yuzhang Shang

    cs.RO · cs.AI · cs.CV

    Learning reliable surgical manipulation policies is bottlenecked by the scarcity of action-labeled demonstrations: teleoperated surgical robot (e.g., dVRK) trajectories with synchronized kinematics are costly to collect, while surgical tasks demand precise contact handling, long-horizon reasoning, and bimanual coordination. Endoscopic video is comparatively inexpensive and abundant relative to synchronized video--kinematics trajectories, and...

    arxiv.org/abs/2608.11204 · PDF

  2. 02

    BooST: Bridging Semantics and Motions for Efficient Skill Transfer

    Jusuk Lee, Daesol Cho, Jonghun Shin, Seungyeon Yoo, Jonghae Park, Taekbeom Lee, H. Jin Kim

    cs.RO · cs.CV · cs.LG

    Skill abstraction---the process of learning reusable and temporally extended behaviors---has emerged as a key paradigm for improving sample efficiency and generalization in robot learning. For efficient skill transfer to real robots, learned skills must generalize across tasks and domains, remain robust to visual and dynamic perturbations, and be efficient enough for practical deployment. However, existing methods typically satisfy only a...

    arxiv.org/abs/2608.10600 · PDF

  3. 03

    Lost in Reconstruction: Aligning Action Representations with Language in Vision-Language-Action Models

    Li Wenjie, Yash Jangir, Ignacy Stepka, Yash Agarwal, Marion Kipsang, Yonatan Bisk

    cs.RO · cs.AI · cs.CL

    Action verbs describe not only the physical outcomes of actions, but also how those actions are performed. Yet action representations in vision-language-action models (VLAs) are typically optimized for reconstruction under L1/L2 losses in raw action space, where numerical proximity need not reflect linguistically meaningful distinctions. On BridgeV2, we show that action trajectories contain verb-grounding information beyond visual state...

    arxiv.org/abs/2608.10484 · PDF

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