SlotRefine: A Fast Non-Autoregressive Model forJoint Intent Detection and Slot Filling

Related tags

Deep Learning SlotRefine
Overview

SlotRefine: A Fast Non-Autoregressive Model for Joint Intent Detection and Slot Filling

Reference

Main paper to be cited (Di Wu et al., 2020)

@article{wu2020slotrefine,
  title={Slotrefine: A fast non-autoregressive model for joint intent detection and slot filling},
  author={Wu, Di and Ding, Liang and Lu, Fan and Xie, Jian},
  booktitle={EMNLP},
  year={2020}
}

Requirements

Our system is build upon the THUMT codebase.

tensorflow 1.12
python 3.6

Usage

sh train.atis.sh

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Comments
  • question

    question

    It's a nice work to use non-autoregressive model to solve joint intent detection and slot filling problem. I have a problem about two-pass refine mechanism. As you say in Figure1: In the first pass, wrong slot tagging results are predicted, as shown in the pink dotted box in the figure, and the “B-tags” (beginning tag of a slot) are feeded as additional information with utterance for second iteration.

    I am very curious about the effect if the prediction results of the first pass are directly used as input to the second pass (i.e., not only B-tags. We copy the result of the first pass).

    Finally I am looking forward to your code. Thank you!

    opened by wjczf123 3
  • SlotRefine with BERT

    SlotRefine with BERT

    Hi!

    I noticed that in the results of your work, you have a version of SlotRefine with BERT.

    Is it possible to share the code used to obtain the results for SlotRefine with BERT?

    Thank you!

    opened by ehealthz-lab 0
Owner
Moore
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Moore
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