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20202026
most citedKnowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control

21 citations · 66 across the 27 of their papers we have counts for

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5 papers · 1 filter

cs.RO2026

Encoded but Not in Control: Revealing the Grounding Gap in Vision-Language Robot Policies

Shaohan Jiang, Jiahang Cao, Qiduo He +9

Instruction following is central to language-conditioned robot policies: language should determine what to do when the same scene permits multiple valid actions. Yet successful exe…

cs.RO2026

A Causality-aware Infer-diagnose-refine Framework for Test-time Modality Adaptation in VLA Models

Haoyu Zhang, Yuwei Wu, Jin Chen +6

Vision-language-action (VLA) models predict sequential actions to execute tasks specified by language instructions, conditioned on visual observations and proprioceptive states. Ho…

cs.RO2026

HEX: Humanoid-Aligned Experts for Cross-Embodiment Whole-Body Manipulation

Shuanghao Bai, Meng Li, Xinyuan Lv +15

Humans achieve complex manipulation through coordinated whole-body control, whereas most Vision-Language-Action (VLA) models treat robot body parts largely independently, making hi…

cs.RO2026

RoboGene: Boosting VLA Pre-training via Diversity-Driven Agentic Framework for Real-World Task Generation

Yixue Zhang, Kun Wu, Zhi Gao +12

The pursuit of general-purpose robotic manipulation is hindered by the scarcity of diverse, real-world interaction data. Unlike data collection from web in vision or language, robo…

cs.RO2026

RoboAug: One Annotation to Hundreds of Scenes via Region-Contrastive Data Augmentation for Robotic Manipulation

Xinhua Wang, Kun Wu, Zhen Zhao +10

Enhancing the generalization of robotic learning in diverse unseen environments remains a fundamental challenge. Existing approaches often rely on large-scale pretraining, which is…