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多模态问题解答

多模态问题解答（Multimodal QA）是一类深度学习方法，它通过联合推理文本和图像（最常见）、视频、音频及结构化表格等多种模态的信息来回答自然语言问题。该领域由 VQA 基准在 2015 年首次提出，现已发展成为一个广泛的研究领域，应用于文档理解、医疗诊断辅助和具身人工智能等。

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多模态问题解答
[需翻译标题：BERT-based Classi…多模态BERT分类多模态句子嵌入多模态文本摘要多模态Transformer多模态命名实体识别

来源

  1. Antol, S., Agrawal, A., Lu, J., Mitchell, M., Batra, D., Zitnick, C. L., & Parikh, D. (2015). VQA: Visual Question Answering. Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2425–2433. DOI: 10.1109/ICCV.2015.279 ↗
  2. Xu, P., Zhu, X., & Clifton, D. A. (2023). Multimodal learning with transformers: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(10), 12113–12132. DOI: 10.1109/TPAMI.2023.3275156 ↗

如何引用本页

ScholarGate. (2026, June 3). Multimodal Question Answering (Cross-Modal QA). ScholarGate. https://scholargate.app/zh/deep-learning/multimodal-question-answering

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多模态命名实体识别多模态文本摘要

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ScholarGate — Multimodal question answering (Multimodal Question Answering (Cross-Modal QA)). 于 2026-06-15 检索自 https://scholargate.app/zh/deep-learning/multimodal-question-answering · 数据集： https://doi.org/10.5281/zenodo.20539026