41 citations · 113 across the 29 of their papers we have counts for
13 papers · 1 filter
SynDoc: A Hybrid Discriminative-Generative Framework for Enhancing Synthetic Domain-Adaptive Document Key Information Extraction
Yihao Ding, Soyeon Caren Han, Yanbei Jiang +3
Domain-specific Visually Rich Document Understanding (VRDU) presents significant challenges due to the complexity and sensitivity of documents in fields such as medicine, finance,…
VRD-IU: Lessons from Visually Rich Document Intelligence and Understanding
Yihao Ding, Soyeon Caren Han, Yan Li +1
Visually Rich Document Understanding (VRDU) has emerged as a critical field in document intelligence, enabling automated extraction of key information from complex documents across…
SynJAC: Synthetic-data-driven Joint-granular Adaptation and Calibration for Domain Specific Scanned Document Key Information Extraction
Yihao Ding, Soyeon Caren Han, Zechuan Li +1
Visually Rich Documents (VRDs), comprising elements such as charts, tables, and paragraphs, convey complex information across diverse domains. However, extracting key information f…
PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering
Yihao Ding, Kaixuan Ren, Jiabin Huang +2
Document Question Answering (QA) presents a challenge in understanding visually-rich documents (VRD), particularly those dominated by lengthy textual content like research journal…
SCO-VIST: Social Interaction Commonsense Knowledge-based Visual Storytelling
Eileen Wang, Soyeon Caren Han, Josiah Poon
Visual storytelling aims to automatically generate a coherent story based on a given image sequence. Unlike tasks like image captioning, visual stories should contain factual descr…
PiggyBack: Pretrained Visual Question Answering Environment for Backing up Non-deep Learning Professionals
Zhihao Zhang, Siwen Luo, Junyi Chen +4
We propose a PiggyBack, a Visual Question Answering platform that allows users to apply the state-of-the-art visual-language pretrained models easily. The PiggyBack supports the fu…