arXiv cs.CV
· Papers
TSHA: A Benchmark for Visual Language Models in Trustworthy Safety Hazard Assessment Scenarios
arXiv:2603.29759v3 Announce Type: replace Abstract: Recent advances in vision-language models (VLMs) have accelerated their application to indoor safety hazards assessment. However, existing benchmarks suffer from three fundamental limitations: (1) heavy reliance on synthetic datasets constructed via simulation softwar