在知乎的这个回答中找到的一个答案:
Transformer模型之所以被称为"Transformer",是因为它的核心功能是对输入数据的矩阵进行变换处理。这种变换是通过计算矩阵内部各个向量之间的关系来实现的,目的是去除无效信息并加强有效信息。在这个过程中,组成矩阵的向量的值会发生变化,但形状保持不变。这样的变换使得模型能够更好地解决最终问题
来自 ChatGPT 的回答:
The term "transformer" comes from the model’s core function—it transforms input data (like a sequence of words) into a new, more useful representation for a given task. Introduced in the influential paper "Attention Is All You Need," the transformer architecture uses attention mechanisms to "re-cast" or transform each element of the input sequence by dynamically relating it to other elements. This ability to flexibly transform input data into contextually enriched representations is a key reason behind its name.
DeepSeek的回答:
Transformer 模型架构之所以命名为 "Transformer",是因为其核心机制通过自注意力(self-attention)对输入序列中不同位置的关联信息进行动态转换和整合,从而实现对全局上下文的高效建模。
豆包的回答:
Transformer 模型名称源于其通过自注意力机制动态转换输入序列的表示形式,从而高效处理长距离依赖关系的核心能力。
ChatGPT 的回答:
It's called a "transformer" because it transforms input data into contextually enriched representations using attention mechanisms.
提示词中加了“用一句话回答”
Why transformer in deep learning is called transformer?
– dudu 1周前