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GIFT: Goal-Injected Fine-Tuning for Efficient Manipulation Policy Adaptation

arXiv · AI, language, vision and robotics · article · Sep 7, 2026 · UTC

Compared with relying solely on initial observations and language instructions, predicting goal images with generative models as high-level visual guidance can significantly enhance the robustness of Vision-Language-Action (VLA) models. However, most existing foundation models have not systematically incorporated goal image conditioning due to the high computational training cost. To this end, we propose Goal-Injected Fine-Tuning (GIFT), a lightweight and efficient fine-tuning framework that seamlessly integrates generated goal images into multiple representative pretrained VLA models. Our app

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