LADBench: A Benchmark for Logical Fault Detection in Images

Name: LADBench: A Benchmark for Logical Fault Detection in Images
Uploaded: 2026-10-22T01:57:14.008758+00:00
Duration: 327 s
Description: LAD-Bench introduces a benchmark of over 1,000 synthetic images with logical anomalies across four domains: Residential, Urban, Collaborative, and Nature. It uses a Tiered Prompting Protocol to measure how much explicit guidance models need to find physical or social inconsistencies. The results show current Vision-Language Models struggle with implicit logical fault detection.

LAD-Bench introduces a benchmark of over 1,000 synthetic images with logical anomalies across four domains: Residential, Urban, Collaborative, and Nature. It uses a Tiered Prompting Protocol to measure how much explicit guidance models need to find physical or social inconsistencies. The results show current Vision-Language Models struggle with implicit logical fault detection.

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