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Found 4 papers, 1 papers with code
Your Large Vision-Language Model Only Needs A Few Attention Heads For Visual Grounding
However, we discover that a few attention heads in frozen LVLMs demonstrate strong visual grounding capabilities.
See What You Are Told: Visual Attention Sink in Large Multimodal Models
Large multimodal models (LMMs) "see" images by leveraging the attention mechanism between text and visual tokens in the transformer decoder.
WoLF: Wide-scope Large Language Model Framework for CXR Understanding
(1) Previous methods solely use CXR reports, which are insufficient for comprehensive Visual Question Answering (VQA), especially when additional health-related data like medication history and prior diagnoses are needed.
Reading Books is Great, But Not if You Are Driving! Visually Grounded Reasoning about Defeasible Commonsense Norms
NORMLENS consists of 10K human judgments accompanied by free-form explanations covering 2K multimodal situations, and serves as a probe to address two questions: (1) to what extent can models align with average human judgment?
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