6 papers
MonkeyOCRv2: A Visual-Text Foundation Model for Document AI
Yuliang Liu, Zhang Li, Ziyang Zhang +11
Mainstream visual encoders are pretrained on natural images and cannot be effectively applied to document images without document-oriented adaptation, as dense text and fine-graine…
EarlyTom: Early Token Compression Completes Fast Video Understanding
Hesong Wang, Xin Jin, Lu Lu +4
Video large language models (Video-LLMs) have demonstrated strong capabilities in video understanding tasks. However, their practical deployment is still hindered by the inefficien…
MDPBench: A Benchmark for Multilingual Document Parsing in Real-World Scenarios
Zhang Li, Zhibo Lin, Qiang Liu +7
We introduce Multilingual Document Parsing Benchmark, the first benchmark for multilingual digital and photographed document parsing. Document parsing has made remarkable strides,…
MonkeyOCR: Document Parsing with a Structure-Recognition-Relation Triplet Paradigm
Zhang Li, Yuliang Liu, Qiang Liu +8
We introduce MonkeyOCR, a document parsing model that advances the state of the art by leveraging a Structure-Recognition-Relation (SRR) triplet paradigm. This design simplifies wh…
MonkeyOCR v1.5 Technical Report: Unlocking Robust Document Parsing for Complex Patterns
Jiarui Zhang, Yuliang Liu, Zijun Wu +17
Document parsing is a core task in document intelligence, supporting applications such as information extraction, retrieval-augmented generation, and automated document analysis. H…
LIRA: Inferring Segmentation in Large Multi-modal Models with Local Interleaved Region Assistance
Zhang Li, Biao Yang, Qiang Liu +7
While large multi-modal models (LMMs) demonstrate promising capabilities in segmentation and comprehension, they still struggle with two limitations: inaccurate segmentation and ha…