12 citations · 21 across the 10 of their papers we have counts for
12 papers
LongHisDoc: A Comprehensive Benchmark for Chinese Long Historical Document Understanding
Zeyu Shan, Yongxin Shi, Shihang Wu +4
Chinese historical documents are invaluable cultural treasures, but their complexity poses significant comprehension challenges for non-specialists. Despite the success of Large La…
DocIntent: Answerability-Guided Agentic Restoration for Real-World Document Visual Question Answering
Zihan Huang, Shihang Wu, Junle Liu +4
Real-world degradations such as blur, shadow, distortion, and moire patterns severely impair the document question-answering capabilities of Multimodal Large Language Models (MLLMs…
One Patch Is Enough: Reinforcement-Optimized Visual Token Grounding for MLLM-Based Scene Text Spotting
Rui Tang, Wentao Yang, Peirong Zhang +4
Scene text spotting requires high-precision alignment between textual recognition and spatial localization. While visual-token grounding has emerged as a promising formulation for…
URaG: Unified Retrieval and Generation in Multimodal LLMs for Efficient Long Document Understanding
Yongxin Shi, Jiapeng Wang, Zeyu Shan +3
Recent multimodal large language models (MLLMs) still struggle with long document understanding due to two fundamental challenges: information interference from abundant irrelevant…
Reviving Cultural Heritage: A Novel Approach for Comprehensive Historical Document Restoration
Yuyi Zhang, Peirong Zhang, Zhenhua Yang +5
Historical documents represent an invaluable cultural heritage, yet have undergone significant degradation over time through tears, water erosion, and oxidation. Existing Historica…
MegaHan97K: A Large-Scale Dataset for Mega-Category Chinese Character Recognition with over 97K Categories
Yuyi Zhang, Yongxin Shi, Peirong Zhang +3
Foundational to the Chinese language and culture, Chinese characters encompass extraordinarily extensive and ever-expanding categories, with the latest Chinese GB18030-2022 standar…
OCR-Reasoning Benchmark: Unveiling the True Capabilities of MLLMs in Complex Text-Rich Image Reasoning
Mingxin Huang, Yongxin Shi, Dezhi Peng +3
Recent advancements in multimodal slow-thinking systems have demonstrated remarkable performance across various visual reasoning tasks. However, their capabilities in text-rich ima…
Predicting the Original Appearance of Damaged Historical Documents
Zhenhua Yang, Dezhi Peng, Yongxin Shi +3
Historical documents encompass a wealth of cultural treasures but suffer from severe damages including character missing, paper damage, and ink erosion over time. However, existing…
TongGu: Mastering Classical Chinese Understanding with Knowledge-Grounded Large Language Models
Jiahuan Cao, Dezhi Peng, Peirong Zhang +4
Classical Chinese is a gateway to the rich heritage and wisdom of ancient China, yet its complexities pose formidable comprehension barriers for most modern people without speciali…
CBench: A Comprehensive Classical Chinese Understanding Benchmark for Large Language Models
Jiahuan Cao, Yongxin Shi, Dezhi Peng +2
Classical Chinese Understanding (CCU) holds significant value in preserving and exploration of the outstanding traditional Chinese culture. Recently, researchers have attempted to…
UPOCR: Towards Unified Pixel-Level OCR Interface
Dezhi Peng, Zhenhua Yang, Jiaxin Zhang +5
Existing optical character recognition (OCR) methods rely on task-specific designs with divergent paradigms, architectures, and training strategies, which significantly increases t…
Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation
Yongxin Shi, Dezhi Peng, Wenhui Liao +5
This paper presents a comprehensive evaluation of the Optical Character Recognition (OCR) capabilities of the recently released GPT-4V(ision), a Large Multimodal Model (LMM). We as…