LAMPAT: Low-rank Adaptation Multilingual Paraphrasing using Adversarial Training

About The Project

This is an implementation of LAMPAT: Low-rank Adaptation Multilingual Paraphrasing using Adversarial Training.

LAMPAT has been accepted at the 38th AAAI Conference on Artificial Intelligence (AAAI-24). Paper can be found at this link.

Getting Started

To get started, you should have prior knowledge on Python and PyTorch at first. A few resources to get you started if this is your first Python or PyTorch project:

• PyTorch Tutorials
• Python for Beginners

Installation

1. Clone the repo

   git clone https://github.com/phkhanhtrinh23/LAMPAT.git

2. Use any code editor to open the folder LAMPAT.

Run

1. Create conda virtual environment: conda create -n lampat python=3.8, activate it: conda activate lampat, and install the required packages: pip install -r requirements.txt.

2. Download wmt19_v18

3. Extract the files to .txt files, rename all of the files with their ISO 639-1 code, and place them in the path data/wmt19_v18. For example: data/wmt19_v18/en.txt

4. Read and run train.sh to train the LAMPAT model.

Evaluation

Evaluation dataset

The evaluation dataset can be downloaded at this link

Download the zip file and unzip it to put into the evaluation/eval_dataset

Run

In the evaluation folder, there are 3 python files:

• mev_sup_multi_ref.py: used to evaluate on STAPLE multi-reference evaluation dataset
• mev_sup.py: used to evaluate on PAWS-X and Opusparcus
• mev_unsup.py: used to evaluate on WMT19

Each file will run the metrics and report the score to the console

Contribution

Contributions are what make GitHub such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the project
2. Create your Contribute branch: git checkout -b contribute/Contribute
3. Commit your changes: git commit -m 'add your messages'
4. Push to the branch: git push origin contribute/Contribute
5. Open a pull request

Contact

Email: phkhanhtrinh23@gmail.com

Project Link: https://github.com/phkhanhtrinh23/LAMPAT.git