February 23, 2024Open Access

Transformers：统计解释、架构及应用

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Abstract

Transformers因其先进的多头注意力机制而被广泛认可为分析多任务的强大工具，如自然语言处理（NLP）、计算机视觉（CV）和语音识别（SR）。受其丰富设计和强大功能分析输入数据的启发，我们希望从各种架构入手，进一步探讨其统计机制及推理，然后介绍其在主要任务中的应用。潜在的统计机制引起了我们的兴趣，促使我们以更高层次进行研究，本综述将聚焦其数学基础，并利用这些原理尝试分析其在多种识别场景中卓越表现的原因。

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Fanfei Meng

Yuxin Wang

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Applied and Computational Engineering

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Meng等人（星期五，）研究了这个问题。

www.synapsesocial.com/papers/68e77e02b6db6435876f2018 — DOI: https://doi.org/10.54254/2755-2721/43/20230832

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Proceedings of the 1st Workshop on Evaluating Vector-Space Representations for NLP· 2016 · 19 citations
Sequence to Sequence Learning with Neural Networks· 2014 · 13,337 citations
Weighted Transformer Network for Machine Translation· 2017 · 134 citations

Transformers：统计解释、架构及应用

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