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Finding Label and Model Errors in Perception Data With Learned Observation Assertions

Summary: Introduces learned observation assertions; Fixy audits perception labels. Fixy learns distributions over noisy labels and prior models to score label errors, outperforming baselines with up to 2x precision and uncovering errors in 70% of scenes. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6359
Venue
SIGMOD
Year
2022
Pagerank
5.1943414e-05
Overall Rank
6,134 | 57.33%
DOI
10.1145/3514221.3517907

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