FiberTune is a new fine-tuning objective that preserves action-fiber visual residuals in VLA policies, yielding performance gains on simulation and physical robot tasks.
GenAug: Retargeting behaviors to unseen situ- ations via Generative Augmentation
2 Pith papers cite this work, alongside 2 external citations. Polarity classification is still indexing.
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TREAD augments robotics datasets via VLM-based sub-task generation, video segmentation, and linguistic diversity to improve policy generalization on novel tasks in LIBERO benchmarks.
citing papers explorer
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FiberTune: Preserving Action-Fiber Visual Residuals in Vision-Language-Action Fine-Tuning
FiberTune is a new fine-tuning objective that preserves action-fiber visual residuals in VLA policies, yielding performance gains on simulation and physical robot tasks.
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Task Robustness via Re-Labelling Vision-Action Robot Data
TREAD augments robotics datasets via VLM-based sub-task generation, video segmentation, and linguistic diversity to improve policy generalization on novel tasks in LIBERO benchmarks.