collaborators

7 papers

cs.CL2026

HPD-Parsing: Hierarchical Parallel Document Parsing

Shu Wei, Jingjing Wu, Lingshu Zhang +10

Efficient teamwork typically combines global coordination with parallel execution, a principle not yet fully reflected in unified Vision-Language Model (VLM)-based document parsers…

cs.CV2026

P-MTP: Efficient Document Parsing via Multi-Token Prediction with Progressive Depth Scaling

Le Xiang, Chenxi Zhai, Shu Wei +5

Vision-Language Models (VLMs) have revolutionized document parsing by enabling end-to-end mapping from images to structured text, imposing a significant latency bottleneck, particu…

cs.CV2026

Unlimited OCR Works

Youyang Yin, Huanhuan Liu, YY +14

Recently, end-to-end OCR models, exemplified by DeepSeek OCR, have once again thrust OCR into the spotlight. A widely held view is that employing a large language model (LLM) as th…

cs.CL2025

Post-Completion Learning for Language Models

Xiang Fei, Siqi Wang, Shu Wei +5

Current language model training paradigms typically terminate learning upon reaching the end-of-sequence (<eos>) token, overlooking the potential learning opportunities in the post…

cs.CV2025

MTVQA: Benchmarking Multilingual Text-Centric Visual Question Answering

Jingqun Tang, Qi Liu, Yongjie Ye +14

Text-Centric Visual Question Answering (TEC-VQA) in its proper format not only facilitates human-machine interaction in text-centric visual environments but also serves as a de fac…

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…