Understanding VLM behaviors requires systematic diagnosis—DiaVLo shows how to identify what models actually do versus what they should do, and which concepts drive their decisions.
DiaVLo is a diagnostic framework that identifies and explains the behaviors of vision-language models by comparing desired behaviors against observed ones. It uses human curation and the models' own generation capabilities to surface misalignments and pinpoint which concepts most influence model decisions.