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GATO-Vid achieves superior spatial localization in text-to-video generation without the computational costs of traditional gradient-based methods.
Traditional linear steering methods fail in robotic manipulation, but DiMaS reveals a more effective way to control behavior by matching representation distributions.
LVLMs are often tripped up not by faulty vision, but by over-trusting the textual prompt, leading to surprisingly easy-to-fix hallucinations.
