Hugging Face Trending Papers
Facet-0: A Robotic Foundation Model for Contact-Rich Precise Manipulation
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Facet-0: A Robotic Foundation Model for Contact-Rich Precise Manipulation
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PAC-ACT: Post-training Actor-Critic for Action Chunking Transformers
arXiv:2607. 09590v1 Announce Type: cross Abstract: Precision industrial contact manipulation requires reliable robot policies under pose perturbations and contact-force constraints.
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Play2Perfect: What Matters in Dexterous Play Pretraining for Precise Assembly?
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ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching
ForceFlow is a force-aware reactive framework that uses flow matching to improve contact-rich manipulation. It fuses force signals asymmetrically, treats force as a global regulator, and employs a joint prediction paradigm to couple force and motion. The approach splits tasks into a vision-dominant localization stage and a touch-dominant execution stage, using a Vision-to-Force handover to separate spatial generalization from contact regulation.
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GEAR-VLA: Learning Geometry-Aware Action Representations for Generalizable Robotic Manipulation
arXiv:2606. 08530v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models achieve strong benchmark performance but still struggle in real-world deployment with unseen objects, background shifts, and different robot embodiments.
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HALO-WA: Hybrid-Attention Latent-Guided Online Reinforcement Learning for World-Action Models
arXiv:2607. 04265v1 Announce Type: cross Abstract: World-action (WA) models can generate long-horizon action chunks for general-purpose robotic manipulation, but they remain vulnerable to calibration, perception, and contact-dynamics errors in real-world precision tasks, often failing in the final few millimeters of alignment or insertion.