Mastering Negation: Boosting Grounding Models via Grouped Opposition-Based Learning

ArXi:2603.12606v1 Announce Type: cross Current vision-language detection and grounding models predominantly focus on prompts with positive semantics and often struggle to accurately interpret and ground complex expressions containing negative semantics. A key reason for this limitation is the lack of high-quality