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ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents

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ViDoRAG utilizes multi-agent iterative reasoning and hybrid retrieval strategies to enhance performance in visual document retrieval-augmented generation tasks.

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更新时间:2025-03-05 13:53:54

ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents的信息

什么是ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents

ViDoRAG is a cutting-edge framework developed to handle complex tasks involving visual documents. It combines visual retrieval with text-based reasoning through a dynamic iterative approach, creating a more robust AI system. This framework is particularly useful for tasks where documents contain both textual and visual information, enabling the system to reason over both modalities to generate more accurate and relevant responses.

ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents怎么用?

To use ViDoRAG, first set up the environment by creating a Conda environment and installing dependencies. Then, download the dataset and set up an index database. Use the multi-modal retriever for data retrieval and the multi-agent generation module for generating answers from the retrieved content. You can also perform evaluations with the provided scripts to assess performance on your dataset.

ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents核心功能

  • Multi-agent iterative reasoning for visual document generation
  • Hybrid retrieval strategy combining Gaussian Mixture Models (GMM) with multi-modal retrieval
  • Enhanced robustness against noise in generated answers
  • Integration with OCR models for text extraction from images
  • Support for dynamic retrieval and evaluation pipelines

ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents使用案例

  • Use ViDoRAG for retrieval-augmented generation tasks, especially when handling large and visually rich document collections
  • Integrate ViDoRAG with your own dataset for customized retrieval pipelines
  • Use the framework for large-scale document-based AI applications in research, education, or data management

ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents价格

ViDoRAG is an open-source framework, and its usage and evaluation code are freely available on GitHub.

ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents公司名称

Alibaba-NLP

ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents联系方式

[email protected]

ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents社交媒体

Twitter: @Alibaba_NLP, Instagram: @alibaba_nlp

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