4 citations · 7 across the 12 of their papers we have counts for
5 papers · 1 filter
VASCAR: Content-Aware Layout Generation via Visual-Aware Self-Correction
Jiahao Zhang, Ryota Yoshihashi, Shunsuke Kitada +2
Large language models (LLMs) have proven effective for layout generation due to their ability to produce structure-description languages, such as HTML or JSON. In this paper, we ar…
ReLayout: Towards Real-World Document Understanding via Layout-enhanced Pre-training
Zhouqiang Jiang, Bowen Wang, Junhao Chen +1
Recent approaches for visually-rich document understanding (VrDU) uses manually annotated semantic groups, where a semantic group encompasses all semantically relevant but not obvi…
Putting People in LLMs' Shoes: Generating Better Answers via Question Rewriter
Junhao Chen, Bowen Wang, Zhouqiang Jiang +1
Large Language Models (LLMs) have demonstrated significant capabilities, particularly in the domain of question answering (QA). However, their effectiveness in QA is often undermin…
DiReCT: Diagnostic Reasoning for Clinical Notes via Large Language Models
Bowen Wang, Jiuyang Chang, Yiming Qian +6
Large language models (LLMs) have recently showcased remarkable capabilities, spanning a wide range of tasks and applications, including those in the medical domain. Models like GP…
Explainable Image Recognition via Enhanced Slot-attention Based Classifier
Bowen Wang, Liangzhi Li, Jiahao Zhang +2
The imperative to comprehend the behaviors of deep learning models is of utmost importance. In this realm, Explainable Artificial Intelligence (XAI) has emerged as a promising aven…