Author

L. Krishna

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Preprint Sep 2026

Beyond End-Task Success: How to Audit Visual Experience Retrieval in Robotics

Robots that store past experiences must select which one to reuse in a new scene. Most systems select by visual similarity, and most evaluations report only the success of the selected experience. That number does not show whether the selection was good: a rule can score well by repeatedly using one broadly transferabl...

Eshika Pathak, L. Krishna · 0 citations

#artificial intelligence Preprint Sep 2026

When Should a Failing Robot Ask? Initiating Corrective Human-Robot Dialogue from Audited Sensor Evidence

This work poses the choice as a three-action decision problem, act, consult your own sensors, or ask a human, whose optimal policy follows from measured accuracy, whose optimal policy follows from measured accuracy.

Eshika Pathak, L. Krishna · 0 citations