activity
20232026
most citedMinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing

2 citations · 4 across the 8 of their papers we have counts for

collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV2026

From Diagnosis to Correction: Benchmarking and Improving Real-World Table Parsing

Jutao Xiao, Yuan Qu, Dongsheng Ma +7

Recent document parsers achieve table TEDS scores above 93 on OmniDocBench v1.6, yet community feedback and our audit reveal persistent failures on complex real-world tables. To qu…

cs.CV2026★ 1 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.CV2025★ 2 cited

MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing

Junbo Niu, Zheng Liu, Zhuangcheng Gu +58

We introduce MinerU2.5, a 1.2B-parameter document parsing vision-language model that achieves state-of-the-art recognition accuracy while maintaining exceptional computational effi…

cs.CV2025

Enhancing Video Large Language Models with Structured Multi-Video Collaborative Reasoning

Zhihao He, Tianyao He, Yun Xu +5

Despite the prosperity of the video language model, the current pursuit of comprehensive video reasoning is thwarted by the inherent spatio-temporal incompleteness within individua…

cs.CV2025★ 1 cited

MECD+: Unlocking Event-Level Causal Graph Discovery for Video Reasoning

Tieyuan Chen, Huabin Liu, Yi Wang +5

Video causal reasoning aims to achieve a high-level understanding of videos from a causal perspective. However, it exhibits limitations in its scope, primarily executed in a questi…

cs.CV2024

MECD: Unlocking Multi-Event Causal Discovery in Video Reasoning

Tieyuan Chen, Huabin Liu, Tianyao He +8

Video causal reasoning aims to achieve a high-level understanding of video content from a causal perspective. However, current video reasoning tasks are limited in scope, primarily…

cs.CV2023

Collaborative Weakly Supervised Video Correlation Learning for Procedure-Aware Instructional Video Analysis

Tianyao He, Huabin Liu, Yuxi Li +4

Video Correlation Learning (VCL), which aims to analyze the relationships between videos, has been widely studied and applied in various general video tasks. However, applying VCL…