activity
20242026
most citedInternLM2 Technical Report

29 citations · 54 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

MinerU-Popo: Universal Post-Processing Model for Structured Document Parsing

Bangrui Xu, Ziyang Miao, Xuanhe Zhou +7

VLM-based OCR models have become the de facto choice for document parsing, as they can accurately extract page-level elements (e.g., paragraphs within individual pages) together wi…

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.LG2026

Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale

Yicheng Zou, Dongsheng Zhu, Lin Zhu +174

We introduce Intern-S1-Pro, the first one-trillion-parameter scientific multimodal foundation model. Scaling to this unprecedented size, the model delivers a comprehensive enhancem…

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.CV2024★ 3 cited

OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotations

Linke Ouyang, Yuan Qu, Hongbin Zhou +17

Document content extraction is a critical task in computer vision, underpinning the data needs of large language models (LLMs) and retrieval-augmented generation (RAG) systems. Des…

cs.CV2024★ 19 cited

MinerU: An Open-Source Solution for Precise Document Content Extraction

Bin Wang, Chao Xu, Xiaomeng Zhao +15

Document content analysis has been a crucial research area in computer vision. Despite significant advancements in methods such as OCR, layout detection, and formula recognition, e…

cs.CL2024

LIMP: Large Language Model Enhanced Intent-aware Mobility Prediction

Songwei Li, Jie Feng, Jiawei Chi +3

Human mobility prediction is essential for applications like urban planning and transportation management, yet it remains challenging due to the complex, often implicit, intentions…

cs.CL2024★ 29 cited

InternLM2 Technical Report

Zheng Cai, Maosong Cao, Haojiong Chen +97

The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI). However, replicating such advan…