activity
20242026
most citedMinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing

2 citations · 3 across the 5 of their papers we have counts for

collaborators

11 papers

cs.CV20261 cited

MinerU2.5-Pro: Pushing the Limits of Data-Centric Document Parsing at Scale

Bin Wang, Tianyao He, Linke Ouyang +40

Current document parsing methods advance primarily through model architecture innovation, while systematic engineering of training data remains underexplored. Yet state-of-the-art…

cs.CV2026

PEARL: Personalized Streaming Video Understanding Model

Yuanhong Zheng, Ruichuan An, Xiaopeng Lin +10

Human cognition of new concepts is inherently a streaming process: we continuously recognize new objects or identities and update our memories over time. However, current multimoda…

cs.AI2026

BrowseComp-: A Visual, Vertical, and Verifiable Benchmark for Multimodal Browsing Agents

Huanyao Zhang, Jiepeng Zhou, Bo Li +22

Multimodal large language models (MLLMs), equipped with increasingly advanced planning and tool-use capabilities, are evolving into autonomous agents capable of performing multimod…

cs.CL2026

DocDancer: Towards Agentic Document-Grounded Information Seeking

Qintong Zhang, Xinjie Lv, Jialong Wu +8

Document Question Answering (DocQA) focuses on answering questions grounded in given documents, yet existing DocQA agents lack effective tool utilization and largely rely on closed…

cs.CV2025

DOCR-Inspector: Fine-Grained and Automated Evaluation of Document Parsing with VLM

Qintong Zhang, Junyuan Zhang, Zhifei Ren +8

Document parsing aims to transform unstructured PDF images into semi-structured data, facilitating the digitization and utilization of information in diverse domains. While vision…

cs.CV2025

TRivia: Self-supervised Fine-tuning of Vision-Language Models for Table Recognition

Junyuan Zhang, Bin Wang, Qintong Zhang +13

Table recognition (TR) aims to transform table images into semi-structured representations such as HTML or Markdown. As a core component of document parsing, TR has long relied on…