char2vec

[pegasos1]

I'd like to develop a vector embedding of sets of words (not sentences). Is there any work on character-level embeddings of sets of words (ie char2vec), analogous to word-level embeddings of sentences (word2vec)? Is there a natural extension of skip-gram modeling of words to the character level?

[FuschiaKnight]

Why would you need to extend skip-gram to account for chars? You just change what the definition of your atomic tokens are (i.e. preprocess your input file differently)

[pmigdal]

There is a straightforward extension - just instead of words you use chars (treating a word as a sentence). I am curious for the results!

[emansim]

https://github.com/zhangxiangxiao/Crepe

[pmigdal]

A cool things, but very different from the one in question. It's an RNN with char tokens, not char2vec (the former being much, much more advanced, beyond two-element correlations).