Unverified50% confidenceFactExact time
Standard VLM policies are usually pretrained only on image-text data, and their action capability relies on subsequent fine-tuning or an additional policy head, so their action priors are relatively thin.
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50%
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Long-term
Relevance
10/15/2026
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Related Claims
UnverifiedThe parameters of pretrained VLAs are already highly specialized for action generation; if the same backbone is made to simultaneously handle future prediction and action generation, the gradient directions may conflict with each other, causing the representation to be pulled apart.79% similarUnverifiedA generalist policy refers to a robot policy model pretrained on multiple tasks and scenarios that can be transferred to new instructions, usually based on a vision-language-action (VLA) architecture; existing generalist policies often can only achieve per-task fine-tuning after pretraining, and true zero-shot generalization remains an open problem.76% similarUnverifiedConstructing training data that includes counting, spatial relationships, and fine-grained attributes can mitigate the inherent deficiencies of VLMs at the pre-training stage.73% similarVerifiedAlignment training optimizes the model's statistical behavior in known scenarios rather than establishing formally verifiable security boundaries, and may fail when faced with rare instruction combinations or role-playing frameworks outside the training distribution.72% similar
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