<ul><li>CoT-VLA is a method that incorporates explicit visual chain-of-thought reasoning into vision-language-action models.</li><li>It predicts future image frames autoregressively as visual goals and generates a short action sequence to achieve these goals.</li><li>CoT-VLA outperforms the state-of-the-art VLA model by 17% in real-world manipulation tasks and 6% in simulation benchmarks.</li><li>CoT-VLA is a state-of-the-art 7B VLA that can understand and generate visual and action tokens.</li></ul>

CoT-VLA: Visual Chain-of-Thought Reasoning for Vision-Language-Action Models

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