Kranthi Kumar Singamaneni

A multimodal cross-modal explainable retrieval-augmented generation framework for hallucination-grounded visual question answering

Recent multimodal large language models (MLLMs) have achieved remarkable performance on visual question answering (VQA) and multimodal reasoning tasks. But one overlooked failure case stubbornly persists: when answers require simultaneous synthesis of evidence from natural images...