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Current vision-language models struggle with process understanding in robotic manipulation, but targeted post-training can yield significant improvements.
Illumination variations can destabilize spacecraft pose estimation, but PAID-ViT achieves remarkable robustness by disentangling illumination effects from structural cues.
Ditch the clunky architectures: a single diffusion model can now handle vision, language, and robot control to achieve SOTA manipulation performance.
