AI RESEARCH
AQuA: Toward Strategic Response Generation for Ambiguous Visual Questions
arXiv CS.CL
•
ArXi:2603.07394v1 Announce Type: cross Visual Question Answering (VQA) is a core task for evaluating the capabilities of Vision-Language Models (VLMs). Existing VQA benchmarks primarily feature clear and unambiguous image-question pairs, whereas real-world scenarios often involve varying degrees of ambiguity that require nuanced reasoning and context-appropriate response strategies. Although recent studies have begun to address ambiguity in VQA, they lack (1) a systematic categorization of ambiguity levels and (2) datasets and models that strategy-aware responses. In this paper, we.