This paper is a good illustration of what I see as a critical shortcoming of modern NLP work: it is all about math and algorithms, there is nothing about actual language.
The paper has lots of information about: neural network architectures, parameter update equations, learning rules, and inference algorithms.
There is nothing about: part of speech categories, relative clauses, morphology, affixes or compound words, the theta criterion, the content/function distinction, verb tenses, agreement, or anything else related to actual linguistic phenomena.
To me this seems a bit like the Aristotelian thinkers who tried to reason about physics based on pure mathematical analysis, without any empirical work.
The paper has lots of information about: neural network architectures, parameter update equations, learning rules, and inference algorithms.
There is nothing about: part of speech categories, relative clauses, morphology, affixes or compound words, the theta criterion, the content/function distinction, verb tenses, agreement, or anything else related to actual linguistic phenomena.
To me this seems a bit like the Aristotelian thinkers who tried to reason about physics based on pure mathematical analysis, without any empirical work.