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20232026
most citedFew-shot Shape Recognition by Learning Deep Shape-aware Features

1 citations · 1 across the 6 of their papers we have counts for

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cs.RO2026

CarryOn: A Dual-Loop Harness for Personalized and Reliable Robot Assistance

Zixuan Wang, Yuqi Liu, Yuxin Chen +7

While generalist vision-language-action (VLA) models have enabled diverse open-world manipulation, real-world robotic assistance requires two critical capabilities they currently l…

cs.RO2026

Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models

Senqiao Yang, Chengyao Wang, Yuxin Chen +13

Scaling robot data is crucial for building generalist Vision-Language-Action (VLA) models, yet robot trajectories are harder to scale than web-scale image-text data because embodie…

cs.CV2026

GKDT: General Keypoint Detection Transformer

Changsheng Lu, Yuxin Chen, Haokun Gui +5

With the emergence of various pre-trained vision and language models, computer vision is shifting from narrow-domain to open-domain recognition. The construction of a more powerful…

cs.CV2026

AHPA: Adaptive Hierarchical Prior Alignment for Diffusion Transformers

Ruibin Min, Yexin Liu, Aimin Pan +5

Representation alignment has recently emerged as an effective paradigm for accelerating Diffusion Transformer training. Despite their success, existing alignment methods typically…

cs.RO2026

VP-VLA: Visual Prompting as an Interface for Vision-Language-Action Models

Zixuan Wang, Yuxin Chen, Yuqi Liu +6

Vision-Language-Action (VLA) models typically map visual observations and linguistic instructions directly to control signals. This "black-box" mapping forces a single forward pass…