2 citations · 2 across the 2 of their papers we have counts for
4 papers
OmniParser V2: Structured-Points-of-Thought for Unified Visual Text Parsing and Its Generality to Multimodal Large Language Models
Wenwen Yu, Zhibo Yang, Jianqiang Wan +5
Visually-situated text parsing (VsTP) has recently seen notable advancements, driven by the growing demand for automated document understanding and the emergence of large language…
GeoFocus: Blending Efficient Global-to-Local Perception for Multimodal Geometry Problem-Solving
Linger Deng, Yuliang Liu, Wenwen Yu +4
Geometry problem-solving remains a significant challenge for Large Multimodal Models (LMMs), requiring not only global shape recognition but also attention to intricate local relat…
DocThinker: Explainable Multimodal Large Language Models with Rule-based Reinforcement Learning for Document Understanding
Wenwen Yu, Zhibo Yang, Yuliang Liu +1
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in document understanding. However, their reasoning processes remain largely black-box, making it…
OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models
Yuliang Liu, Zhang Li, Mingxin Huang +7
Large models have recently played a dominant role in natural language processing and multimodal vision-language learning. However, their effectiveness in text-related visual tasks…