changleilei / AMR-Dialogue

Code for our paper "Semantic Representation for Dialogue Modeling" in ACL2021

AMR-Dialogue

An implementation for paper "Semantic Representation for Dialogue Modeling". You may find our paper here.

Requirements

• python 3.6
• pytorch 1.6
• Tesla V100 (32G)
• Memory > 150G (for DialogRE)

We recommend to use conda to manage virtual environments:

conda create --name <env> --file requirements.txt

Data

The preprocessed data for DialogRE and DialogRG are avaliable at here and here, respectively.

Preprocessing

bash /path/to/code/preprocess.sh

Training

bash /path/to/code/run-dual(hier).sh

Evaluation

bash /path/to/code/eval.sh                   # for dialogue relation extraction
bash /path/to/code/decode.sh                 # for dialogue response generation

Pretrained Models

DialogRE

Data-v1

Setting	dev-F1	dev-F1c	test-F1	test-F1c	checkpoint
Hier	68.3	62.9	68.4	62.3	model
Dual	68.6	62.6	68.0	61.5	model

Data-v2

Setting	dev-F1	dev-F1c	test-F1	test-F1c	checkpoint
Hier	68.8	62.4	66.6	61.2	model
Dual	68.4	62.7	67.3	61.7	model

Todo

• clean code

References

@inproceedings{bai-etal-2021-semantic,
    title = "Semantic Representation for Dialogue Modeling",
    author = "Bai, Xuefeng  and
      Chen, Yulong  and
      Song, Linfeng  and
      Zhang, Yue",
    booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.acl-long.342",
    doi = "10.18653/v1/2021.acl-long.342",
    pages = "4430--4445"
}