A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf
.
A survey of joint intent detection and slot-filling models in natural language understanding
[article]
2021
arXiv
pre-print
Intent classification and slot filling are two critical tasks for natural language understanding. Traditionally the two tasks have been deemed to proceed independently. However, more recently, joint models for intent classification and slot filling have achieved state-of-the-art performance, and have proved that there exists a strong relationship between the two tasks. This article is a compilation of past work in natural language understanding, especially joint intent classification and slot
arXiv:2101.08091v3
fatcat:ai6w2imilrfupf4m5fm2rjtzxi