AI RESEARCH
TINS: Test-time ID-prototype-separated Negative Semantics Learning for OOD Detection
arXiv CS.CV
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ArXi:2605.10756v1 Announce Type: new Vision-language models enable OOD detection by comparing image alignment with ID labels and negative semantics. Existing negative-label-based methods mainly rely on static negative labels constructed before inference, limiting their ability to cover diverse and evolving OOD concepts. Although test-time expansion provides a natural solution, naively learning negative semantics from potential OOD samples may