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What Would Removing This Corruption Change? Failure Attribution for Vision-Language-Action Models
Carson Sobolewski, Anjali Parashar, Fei Chen +2
Vision-language-action (VLA) models are sensitive to visual corruptions, but knowing that a corruption is typically harmful does not establish whether removing it would benefit the…
Bayesian Active Learning for Intent Disambiguation in Interactive Robot Planning
Huao Li, Carson Sobolewski, Augustinos Saravanos +3
Interactive robot planning requires robots to infer and execute human intentions from natural language instructions that are often ambiguous, incomplete, or underspecified. Althoug…
Coverage Aware Active Evaluation for Failure Discovery with Paired Systems
Anjali Parashar, Rachel Luo, Apoorva Sharma +6
Autonomous systems can fail in rare and heterogeneous ways, making real-world failure discovery difficult under limited testing budgets. Although cheaper proxies such as simulators…