Incidental Supervision from Question-Answering Signals

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Other Links: arxiv.org

Abstract:

Human annotations are costly for many natural language processing (NLP) tasks, especially for those requiring NLP expertise. One promising solution is to use natural language to annotate natural language. However, it remains an open problem how to get supervision signals or learn representations from natural language annotations. This p...More

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