A Co-Interactive Transformer for Joint Slot Filling and Intent Detection

This repository contains the PyTorch implementation of the paper:

A Co-Interactive Transformer for Joint Slot Filling and Intent Detection. Libo Qin, TaiLu Liu, Wanxiang Che, bingbing Kang, Sendong Zhao, Ting Liu.

If you use any source codes or the datasets included in this toolkit in your work, please cite the following paper. The bibtex are listed below:

In the following, we will guide you how to use this repository step by step.

Architecture

Results

Preparation

Our code is based on PyTorch 1.2 It can run in PyTorch 1.13.1 right now! (by boyan1001). Required python packages:

• numpy==1.18.1
• tqdm==4.32.1
• torch==1.2.0 (torch==1.13.1)
• (Optional) cuda==12.3

We highly suggest you using Anaconda to manage your python environment.

How to run training:

1. Setting env

conda env create -f environment.yml

2. Run main_joint.py

python main_joint.py

Change dataset:

1. Modify data_path in config.py

If you have any question, please issue the project or email me and we will reply you soon.