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300+篇文献!一文详解基于Transformer的多模态学习最新进展
2022-07-03 03:58:00 【智源社区】
论文地址:
https://arxiv.org/abs/2206.06488
摘要
Transformer 是一种很有前途的神经网络学习器,在各种机器学习任务中取得了巨大的成功。由于最近多模态应用和大数据的流行,基于 Transformer 的多模态学习已成为人工智能研究的热门话题。
本文对面向多模态数据的 Transformer 技术进行了全面调查。本文的主要内容包括:1)多模态学习、Transformer 生态系统和多模态大数据时代的背景;2)从一个几何拓扑视角进行 Vanilla Transformer、Vision Transformer 和 multimodal Transformer 的理论回顾;3)通过两个重要范式,即多模态预训练和特定多模态任务,对多模态 Transformer 应用的回顾;4)对多模态 Transformer 模型和应用所共有的共同挑战和设计的总结,以及 5)对社区的开放问题和潜在研究方向的讨论。
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