Cross-Attention Multitasking Framework for Definition Modeling

Source code for the paper BLCU-ICALL at SemEval-2022 Task 1: Cross-Attention Multitasking Framework for Definition Modeling published on NAACL 2022 Workshop.

Requirements

Training & Evaluation Environment

Pytorch
tokenizers
moverscore
NLTK

In order to install them, you can run this command:

pip install -r requirements.txt

Usage

Download CoDWoE Data from CoDWoE Data Repository
Place the data file(s) anywhere you like, and modify DATA_DIR in the provided shell scripts for training and testing.
To train the model, simply use train.sh by:

./train.sh

To test the model, use the corresponding script test-{lang}.sh. English for example:

./test-en.sh

Cite

@inproceedings{kong-etal-2022-semeval,
    title = "BLCU-ICALL at SemEval-2022 Task 1: Cross-Attention Multitasking Framework for Definition Modeling",
    author = "Kong, Cunliang and
        Wang, Yujie and
        Chong, Ruining and
        Yang, Liner and
        Zhang, Hengyuan and
        Yang, Erhong and
        Huang, Yaping",
    booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
    year = "2022",
    publisher = "Association for Computational Linguistics",
}

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