Show HN: Subsequential Transducer for Efficient Text Rewriting

Came here to ask the same question, I'm not clear on what functionality this offers beyond a simple k-v substitution.

I am not yet 100% certain so I requested full-text access to read the paper, but I can say that a naive approach to string substitution will certainly be less performant than this, and offer less flexibility in replacement complexity without significant effort.

The reason being that in a naive approach, a vocabulary of size M and a document of token size N is an O(m*n) operation in the best case - while this is claimed to be an operation of O(2n).

What specifically do you want to do with these documents?

What would it do that some basic templating library wouldn't do?

Not knowing the specifics, I would lean toward a template library, as it would be more precise, and could account for things like changing gender, plurality, a vs an, etc, in a structured way.

Hi, thanks! The outputs are encoded in the transitions and the states themselves, so the vocabulary size doesn't affect the search. It affects, however, the construction because for each node in the trie we have to add an outgoing transition for each distinct symbol of the input vocabulary.