Vision-language-action (VLA) robustness is commonly summarized by aggregate task success, which obscures how individual executions change under distribution shifts and where failures emerge in long-horizon tasks. We introduce \textbf{RoboCasa-Shift}, a diagnostic robustness benchmark built on RoboCasa365 that combines controlled single-factor shifts, matched clean-perturbed rollouts in which each pair shares the same underlying settings and differs only…
ORIGINAL PAPER
RoboCasa-Shift: Stage-Aware Robustness Evaluation of Vision-Language-Action Policies in Long-Horizon Household Manipulation
WHAT WE KNOW
We introduce \textbf{RoboCasa-Shift}, a diagnostic robustness benchmark built on RoboCasa365 that combines controlled single-factor shifts, matched clean-perturbed rollouts in which each pair shares the same underlying settings and differs only in the target shift, and simulator-grounded stage-aware diagnostics. We evaluate GR00T N1.
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Review the primary source, validate the main result, and establish whether any listed-company transmission is direct.
EVIDENCE
What the evidence supports so far
Research signals
VLA
manipulation
What remains unverified
The full methodology, effect size, and limitations still require analyst review.
Company impact remains unverified until a direct economic transmission is established.