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0111 · Oct 201919922001200920172026
2 results for entity-centric

VB-Score evaluates AI systems without ground truth, revealing robustness.

problem Evaluating AI systems without ground truth labels, especially for entity-centric tasks.
method VB-Score uses variance-bounded evaluation, constraint relaxation, and Monte Carlo sampling.
result VB-Score reveals robustness differences not seen by conventional frameworks.

This paper tests the hypothesis that modeling a scene in terms of entities and their local interactions, as opposed to modeling the scene globally, provides a significant benefit in generalizing to physical tasks in a combinatorial space the learner has not encountered before. We present object-centric perception, pred…

2019-10-28abs ↗pdf ↗