Efficient Intent Detection with Dual Sentence Encoders.

Casanueva, I., Temčinas, T., Gerz, D., Henderson, M., & Vulić, I. (2020). Efficient Intent Detection with Dual Sentence Encoders. Proceedings of the 2nd Workshop on NLP for Conversational AI, 38-45.

Type

Conference paper

Intellectual base

Primary research

Year

2020

DOI

10.18653/v1/2020.nlp4convai-1.5

Link

https://doi.org/10.18653/v1/2020.nlp4convai-1.5

Cited from

sociology_anthropology

Cited by

1 citation across 1 artifact.

Primes

• Native-Category Flattening
  • Consider building a labeled dataset of customer-support messages where the source — the customers — partition their problems into fine native categories ("the app logs me out mid-purchase," "it logs me out overnight") that a coarse label set would conflate; the pair is this entry's own illustration, though real support-intent data does carry just this kind of partially overlapping, fine-grained distinction — reverted top-up versus failed top-up.

Verification

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Registry ID ref:5251143235c8 · see in the full table