This forum post introduces TAG (Target-Agnostic Guidance), a robotics research paper (arXiv:2603.24584) in computer vision. Vision-Language-Action (VLA) policies have shown strong progress in mapping language instructions and visual observations to robotic actions, yet their reliability degrades in cluttered scenes containing distractors. TAG is proposed as a simple inference-time guidance mechanism to improve robustness without requiring retraining. The post includes a brief overview in Chinese, paper metadata (author Zhihao Zhan, released 2026-03-25), and a link to the arXiv abstract. It was automatically collected on 2026-03-27 for zhichai.net readers interested in embodied AI, robot learning, and vision-language models.
Research Area: Computer Vision (CV) Author: Zhihao Zhan Release Date: 2026-03-25 arXiv: 2603.24584
Vision-Language-Action (VLA) policies have shown strong progress in mapping language instructions and visual observations to robotic actions, yet their reliability degrades in cluttered scenes with distractors. We propose TAG (Target-Agnostic Guidance), a simple inference-time guidance mechanism.
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*Automatically collected on 2026-03-27.*
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