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cs.CV2026
Focus, Don't Prune: Identifying Instruction-Relevant Regions for Information-Rich Image Understanding
Mincheol Kwon, Minseung Lee, Seonga Choi +7
Large Vision-Language Models (LVLMs) have shown strong performance across various multimodal tasks by leveraging the reasoning capabilities of Large Language Models (LLMs). However…
cs.CV2026
ROAP: A Reading-Order and Attention-Prior Pipeline for Optimizing Layout Transformers in Key Information Extraction
Tingwei Xie, Jinxin He, Yonghong Song
The efficacy of Multimodal Transformers in visually-rich document understanding (VrDU) is critically constrained by two inherent limitations: the lack of explicit modeling for logi…