最近在学习transformer和LSTM进行了一些对比,在summarization问题上,前者和后者的性能有所差异,因此有了一些疑惑。
现在的想法是transformer模型建立依赖关系的能力可能是依旧比较差,比如我们在机器翻译上是从句子到句子,句子之间的依赖,我们看做是较短的依赖;
但summarization任务上需要考虑的是成篇章级别,并且长距离依赖,这时单靠self-attention建模依赖关系可能仍显不足,而这时候lstm的优势反而凸显出来
我猜想是上述的原因导致了lstm和transformer在summarization任务上的性能差异,希望有知友能够指点一下,万分感谢!
Reference
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