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

2 citations · 3 across the 7 of their papers we have counts for

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cs.CV2026

SenseNova-U1.5: Towards Native Unified Visual Intelligence

Haiwen Diao, Jiahao Wang, Chenjing Ding +62

We launch SenseNova-U1.5, an 8B-MoT native unified multimodal model that understands, reasons about, and generates visual content within an encoder-free and VAE-free architecture.…

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.CV20252 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.CV2024

V3Det Challenge 2024 on Vast Vocabulary and Open Vocabulary Object Detection: Methods and Results

Jiaqi Wang, Yuhang Zang, Pan Zhang +31

Detecting objects in real-world scenes is a complex task due to various challenges, including the vast range of object categories, and potential encounters with previously unknown…

cs.CV2024

MMDU: A Multi-Turn Multi-Image Dialog Understanding Benchmark and Instruction-Tuning Dataset for LVLMs

Ziyu Liu, Tao Chu, Yuhang Zang +8

Generating natural and meaningful responses to communicate with multi-modal human inputs is a fundamental capability of Large Vision-Language Models(LVLMs). While current open-sour…

cs.CV2024

Unified Scene Representation and Reconstruction for 3D Large Language Models

Tao Chu, Pan Zhang, Xiaoyi Dong +3

Enabling Large Language Models (LLMs) to interact with 3D environments is challenging. Existing approaches extract point clouds either from ground truth (GT) geometry or 3D scenes…