VLA-Pro improves cross-task generalization in vision-language-action models by storing task-specific LoRA adapters as procedural memories and retrieving/fusing them at inference.
Coral: Scalable multi-task robot learning via lora experts.arXiv preprint arXiv:2603.09298, 2026
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Evo-Depth is a compact VLA model using a lightweight implicit depth encoder from RGB views plus progressive alignment to boost manipulation performance without added hardware.
citing papers explorer
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VLA-Pro: Cross-Task Procedural Memory Transfer for Vision-Language-Action Models
VLA-Pro improves cross-task generalization in vision-language-action models by storing task-specific LoRA adapters as procedural memories and retrieving/fusing them at inference.
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Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model
Evo-Depth is a compact VLA model using a lightweight implicit depth encoder from RGB views plus progressive alignment to boost manipulation performance without added hardware.