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20212026
most citedLLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model

119 citations · 379 across the 62 of their papers we have counts for

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25 papers · 1 filter

cs.CV2024★ 1 cited

InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System for Long-term Streaming Video and Audio Interactions

Pan Zhang, Xiaoyi Dong, Yuhang Cao +26

Creating AI systems that can interact with environments over long periods, similar to human cognition, has been a longstanding research goal. Recent advancements in multimodal larg…

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

Chimera: Improving Generalist Model with Domain-Specific Experts

Tianshuo Peng, Mingsheng Li, Jiakang Yuan +11

Recent advancements in Large Multi-modal Models (LMMs) underscore the importance of scaling by increasing image-text paired data, achieving impressive performance on general tasks.…

cs.CV2024★ 16 cited

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Zhe Chen, Weiyun Wang, Yue Cao +39

We introduce InternVL 2.5, an advanced multimodal large language model (MLLM) series that builds upon InternVL 2.0, maintaining its core model architecture while introducing signif…

cs.CV2024

OCR Hinders RAG: Evaluating the Cascading Impact of OCR on Retrieval-Augmented Generation

Junyuan Zhang, Qintong Zhang, Bin Wang +6

Retrieval-augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating external knowledge to reduce hallucinations and incorporate up-to-date information without…

cs.CV2024

MIA-DPO: Multi-Image Augmented Direct Preference Optimization For Large Vision-Language Models

Ziyu Liu, Yuhang Zang, Xiaoyi Dong +7

Visual preference alignment involves training Large Vision-Language Models (LVLMs) to predict human preferences between visual inputs. This is typically achieved by using labeled d…

cs.CV2024★ 2 cited

DocLayout-YOLO: Enhancing Document Layout Analysis through Diverse Synthetic Data and Global-to-Local Adaptive Perception

Zhiyuan Zhao, Hengrui Kang, Bin Wang +1

Document Layout Analysis is crucial for real-world document understanding systems, but it encounters a challenging trade-off between speed and accuracy: multimodal methods leveragi…

cs.MM2024★ 4 cited

Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction

Qintong Zhang, Bin Wang, Victor Shea-Jay Huang +5

Document parsing (DP) transforms unstructured or semi-structured documents into structured, machine-readable representations, enabling downstream applications such as knowledge bas…

cs.CV2024

PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction

Long Xing, Qidong Huang, Xiaoyi Dong +8

In large vision-language models (LVLMs), images serve as inputs that carry a wealth of information. As the idiom "A picture is worth a thousand words" implies, representing a singl…

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.CV2024

Image Over Text: Transforming Formula Recognition Evaluation with Character Detection Matching

Bin Wang, Fan Wu, Linke Ouyang +5

Formula recognition presents significant challenges due to the complicated structure and varied notation of mathematical expressions. Despite continuous advancements in formula rec…

cs.CY2024★ 1 cited

Navigating the Data Trading Crossroads: An Interdisciplinary Survey

Yi Yu, Jingru Yu, Xuhong Wang +7

Data has been increasingly recognized as a critical factor in the future economy. However, constructing an efficient data trading market faces challenges such as privacy breaches,…

cs.CV2024★ 1 cited

OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text

Qingyun Li, Zhe Chen, Weiyun Wang +37

Image-text interleaved data, consisting of multiple images and texts arranged in a natural document format, aligns with the presentation paradigm of internet data and closely resem…

cs.CV2024★ 3 cited

InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output

Pan Zhang, Xiaoyi Dong, Yuhang Zang +24

We present InternLM-XComposer-2.5 (IXC-2.5), a versatile large-vision language model that supports long-contextual input and output. IXC-2.5 excels in various text-image comprehens…

cs.DL2024★ 4 cited

OpenDataLab: Empowering General Artificial Intelligence with Open Datasets

Conghui He, Wei Li, Zhenjiang Jin +3

The advancement of artificial intelligence (AI) hinges on the quality and accessibility of data, yet the current fragmentation and variability of data sources hinder efficient data…

cs.CV2024

DocGenome: An Open Large-scale Scientific Document Benchmark for Training and Testing Multi-modal Large Language Models

Renqiu Xia, Song Mao, Xiangchao Yan +19

Scientific documents record research findings and valuable human knowledge, comprising a vast corpus of high-quality data. Leveraging multi-modality data extracted from these docum…

cs.AI2024★ 1 cited

DSDL: Data Set Description Language for Bridging Modalities and Tasks in AI Data

Bin Wang, Linke Ouyang, Fan Wu +7

In the era of artificial intelligence, the diversity of data modalities and annotation formats often renders data unusable directly, requiring understanding and format conversion b…

cs.CV2024★ 16 cited

How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

Zhe Chen, Weiyun Wang, Hao Tian +32

In this report, we introduce InternVL 1.5, an open-source multimodal large language model (MLLM) to bridge the capability gap between open-source and proprietary commercial models…

cs.CV2024★ 7 cited

InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD

Xiaoyi Dong, Pan Zhang, Yuhang Zang +21

The Large Vision-Language Model (LVLM) field has seen significant advancements, yet its progression has been hindered by challenges in comprehending fine-grained visual content due…

cs.CV2024

UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition

Bin Wang, Zhuangcheng Gu, Guang Liang +4

The paper introduces the UniMER dataset, marking the first study on Mathematical Expression Recognition (MER) targeting complex real-world scenarios. The UniMER dataset includes a…

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…

cs.CL2024

WanJuan-CC: A Safe and High-Quality Open-sourced English Webtext Dataset

Jiantao Qiu, Haijun Lv, Zhenjiang Jin +23

This paper presents WanJuan-CC, a safe and high-quality open-sourced English webtext dataset derived from Common Crawl data. The study addresses the challenges of constructing larg…

cs.SD2024★ 4 cited

SongComposer: A Large Language Model for Lyric and Melody Generation in Song Composition

Shuangrui Ding, Zihan Liu, Xiaoyi Dong +6

Creating lyrics and melodies for the vocal track in a symbolic format, known as song composition, demands expert musical knowledge of melody, an advanced understanding of lyrics, a…

cs.CV2024★ 10 cited

SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models

Dongyang Liu, Renrui Zhang, Longtian Qiu +16

We propose SPHINX-X, an extensive Multimodality Large Language Model (MLLM) series developed upon SPHINX. To improve the architecture and training efficiency, we modify the SPHINX…