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LLARVA introduces a pioneering instruction tuning method for robotic applications, unifying multiple learning tasks through structured prompts and innovative use of 2-D visual traces to enhance the al
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2026-03-02 11:31:09
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LLARVA: Vision-Action Instruction Tuning Enhances Robot Learning MathJax Example LLARVA: Vision-Action Instruction Tuning Enhances Robot Learning Dantong Niu* , Yuvan Sharma* , Giscard Biamby , Jerome Quenum , Yutong Bai , Baifeng Shi , Trevor Darrell † , Roei Herzig † Berkeley AI Research, UC Berkeley CoRL 2024 arXiv Code Data Real Robot Demonstrations We fine-tune LLARVA with 3 downstream tasks : "pick blue cube", "stack the cubes" and "destack cube" on a real robot. Left: side views from third person. Middle: raw input to LLARVA model. Right: visualization of the predicted 2-D visual traces RLBench Demonstrations We evaluate LLARVA on 18 RLBench tasks, with the selected 3 tasks showing some emergent properties. Left: rendered 3-D videos. Middle: raw input to LLARVA model. Right: visualization of the predicted 2-D visual traces Abstract In recent years, instruction-tuned Large Multimodal Models (L...
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