Unverified50% confidenceFactExact time
VLA models rely excessively on the camera configuration at training time, and once the number or poses of cameras change in the deployment environment, model performance may drop sharply.
1
Sources
50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedWith the falling prices of lightweight VLA models, consumer-grade depth cameras, and VR devices, as well as the proliferation of 3D printing, the barrier to embodied intelligence is rapidly decreasing.72% similarUnverifiedMulti-view baseline methods usually perform reasonably well under the training configuration, but degrade noticeably once the camera set changes.71% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1012758API
curl https://kongchang.com/api/v1/knowledge/claims/1012758MCP
get_claim(id=1012758)