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Omnivta: Visuo-tactile world modeling for contact- rich robotic manipulation

4 Pith papers cite this work. Polarity classification is still indexing.

4 Pith papers citing it

citation-role summary

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citation-polarity summary

fields

cs.RO 4

years

2026 4

roles

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polarities

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representative citing papers

Learning Versatile Humanoid Manipulation with Touch Dreaming

cs.RO · 2026-04-14 · conditional · novelty 5.0

HTD, a multimodal transformer policy trained with behavioral cloning and touch dreaming to predict future tactile latents, achieves a 90.9% relative success rate improvement over baselines on five real-world contact-rich humanoid loco-manipulation tasks.

World Action Models: The Next Frontier in Embodied AI

cs.RO · 2026-05-12 · unverdicted · novelty 4.0

The paper introduces World Action Models as a new paradigm unifying predictive world modeling with action generation in embodied foundation models and provides a taxonomy of existing approaches.

World Model for Robot Learning: A Comprehensive Survey

cs.RO · 2026-04-30 · unverdicted · novelty 3.0

A comprehensive survey that organizes the literature on world models in robot learning, their roles in policy learning, planning, simulation, and video-based generation, with connections to navigation, driving, datasets, and benchmarks.

citing papers explorer

Showing 4 of 4 citing papers.

  • TAMEn: Tactile-Aware Manipulation Engine for Closed-Loop Data Collection in Contact-Rich Tasks cs.RO · 2026-04-08 · unverdicted · none · ref 47

    TAMEn supplies a cross-morphology wearable interface and pyramid-structured visuo-tactile data regime that raises bimanual manipulation success rates from 34% to 75% via closed-loop collection.

  • Learning Versatile Humanoid Manipulation with Touch Dreaming cs.RO · 2026-04-14 · conditional · none · ref 14

    HTD, a multimodal transformer policy trained with behavioral cloning and touch dreaming to predict future tactile latents, achieves a 90.9% relative success rate improvement over baselines on five real-world contact-rich humanoid loco-manipulation tasks.

  • World Action Models: The Next Frontier in Embodied AI cs.RO · 2026-05-12 · unverdicted · none · ref 90

    The paper introduces World Action Models as a new paradigm unifying predictive world modeling with action generation in embodied foundation models and provides a taxonomy of existing approaches.

  • World Model for Robot Learning: A Comprehensive Survey cs.RO · 2026-04-30 · unverdicted · none · ref 73

    A comprehensive survey that organizes the literature on world models in robot learning, their roles in policy learning, planning, simulation, and video-based generation, with connections to navigation, driving, datasets, and benchmarks.