cs.RO · 2026-08-06 · No. 76

Robotics, 2026-08-06.

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

01 — The papers

4 entries
  1. 01

    Explicit Language Memory for Long-Horizon Planning in Vision-Language-Action Models

    Houze Xu, Jizhong Li, Ziyi Ye

    cs.RO · cs.AI · cs.CV

    Vision-language-action (VLA) models provide a unified paradigm for connecting visual perception, language understanding, and robotic control. However, existing VLA models still face major challenges in long-horizon tasks: sparse expert demonstrations constrain cross-task compositional generalization; the non-Markovian nature of long-horizon tasks makes it difficult for policies conditioned only on current observations to maintain temporal...

    arxiv.org/abs/2608.04765 · PDF

  2. 02

    Suppression Sticks, Locality Is Fragile: A Closed-Loop Target-and-Control Audit of Task-Vector Negation in VLA Policies

    Shaoguang Wang, Weiyu Guo, Rushi Dai, Yiren Zhao, Yandong Guo, Hui Xiong

    cs.RO · cs.LG

    Task-vector arithmetic offers a closed-form way to modify a model, yet its behavioral locality remains unclear in closed-loop robot control. We present a target-and-control audit of per-skill task-vector subtraction from multitask vision-language-action (VLA) policies. Across all ten LIBERO-Goal skills, subtraction produces three qualitatively different regimes: target-control separation for five skills, resistance for three, and global...

    arxiv.org/abs/2608.04692 · PDF

  3. 03

    GUARD: Grounding Uncertainty and Ablation-Based Risk Detection for Diffusion-Based VLAs

    Suhas Hegde, Jitendra Yasaswi Bharadwaj Katta

    cs.RO · cs.AI

    Diffusion-based vision-language-action (VLA) policies can generate plausible actions even when their predictions are weakly grounded in the visual and language evidence defining the task. We introduce GUARD, a test-time failure detection method that measures this grounding without modifying the pretrained policy. GUARD estimates the influence of token-indexed entries in the final vision-language model key-value (KV) cache, constructs...

    arxiv.org/abs/2608.04510 · PDF

  4. 04

    Approximate Multi-Objective Search Under Rulebooks

    Omar Muhammetkulyyev, Oren Salzman, Tichakorn Wongpiromsarn

    cs.RO · cs.AI

    Robotic planning often involves multiple objectives with complex priority relationships, such as safety, efficiency, and regulatory compliance. Rulebooks formalize these relationships, allowing partial ordering of objectives that generalizes both Pareto and lexicographic dominance. Computing the full set of rulebook-optimal solutions, however, is computationally expensive. To address this challenge, we introduce the concept of...

    arxiv.org/abs/2608.04398 · PDF

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