3 papers
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…
cs.CL2025
PharmaShip: An Entity-Centric, Reading-Order-Supervised Benchmark for Chinese Pharmaceutical Shipping Documents
Tingwei Xie, Tianyi Zhou, Yonghong Song
We present PharmaShip, a real-world Chinese dataset of scanned pharmaceutical shipping documents designed to stress-test pre-trained text-layout models under noisy OCR and heteroge…