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20242026
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cs.CV2026

UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters

Yongkun Du, Zhineng Chen, Yazhen Xie +6

Text and formulas constitute the core informational components of many documents. Accurately and efficiently recognizing both is crucial for developing robust and generalizable doc…

cs.CV2026

Dolphin-v2: Universal Document Parsing via Scalable Anchor Prompting

Hao Feng, Wei Shi, Ke Zhang +9

Document parsing has garnered widespread attention as vision-language models (VLMs) advance OCR capabilities. However, the field remains fragmented across dozens of specialized mod…

cs.CV2025

TextSquare: Scaling up Text-Centric Visual Instruction Tuning

Jingqun Tang, Chunhui Lin, Zhen Zhao +15

Text-centric visual question answering (VQA) has made great strides with the development of Multimodal Large Language Models (MLLMs), yet open-source models still fall short of lea…

cs.CV2025

Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting

Hao Feng, Shu Wei, Xiang Fei +10

Document image parsing is challenging due to its complexly intertwined elements such as text paragraphs, figures, formulas, and tables. Current approaches either assemble specializ…

cs.CV2025

ParGo: Bridging Vision-Language with Partial and Global Views

An-Lan Wang, Bin Shan, Wei Shi +7

This work presents ParGo, a novel Partial-Global projector designed to connect the vision and language modalities for Multimodal Large Language Models (MLLMs). Unlike previous work…

cs.CV2024

MCTBench: Multimodal Cognition towards Text-Rich Visual Scenes Benchmark

Bin Shan, Xiang Fei, Wei Shi +6

The comprehension of text-rich visual scenes has become a focal point for evaluating Multi-modal Large Language Models (MLLMs) due to their widespread applications. Current benchma…