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Thank you for this very interesting paper and important research question and contribution. I just have a question. Is this model more suitable for long text data/documents and not so suitable for short texts data or data without much context (ex. very short open-ended survey answers)?
Best,
Evelyn
The text was updated successfully, but these errors were encountered:
@Evelynhuang -- thanks for your query. @prodriguezsosa put together some code for looking specifically at open-ended survey answers, actually. See this part of the guide
Assuming you already have some reasonable pretrained embeddings, we found that you can get reasonable ALC embeddings from just a single instance of a term (and its surrounding ~12 words in context)---see the trump/Trump example in the paper. But I'm not sure if that's the sort of thing you're asking about.
If you clarify your use-case a little more, I will try to say something more definitive.
Hi,
Thank you for this very interesting paper and important research question and contribution. I just have a question. Is this model more suitable for long text data/documents and not so suitable for short texts data or data without much context (ex. very short open-ended survey answers)?
Best,
Evelyn
The text was updated successfully, but these errors were encountered: