UPSA

The source code is available at https://osf.io/gn3j2/

Data

The test sentences, generated sentences and the corresponding reference of the Quora dataset are in quora-results/

#Idea

Requirement

python==2.7 cuda 9.0

python packages

nltk
TensorFlow == 1.3.0
numpy
pickle
Rake (pip install python-rake)
zpar (pip install python-zpar, download model file from https://github.com/frcchang/zpar/releases/download/v0.7.5/english-models.zip and extract it to POS/english-models)

run the code:

python source/run.py --exps_dir exps-sampling --exp_name test --use_data_path data/quoradata/test.txt --mode kw-bleu --N_repeat 1 --save_path sa.txt --batch_size 1 --gpu 0 --search_size 50

The sampling results may vary across different machines.

evaluation script

python source/evaluate.py --reference_path quora-results/ref.txt --generated_path quora-results/gen.txt

Cite this paper

@inproceedings{UPSA,
title="Unsupervised Paraphrasing by Simulated Annealing",
author="Xianggen Liu, Lili Mou, Fandong Meng, Hao Zhou, Jie Zhou, Sen Song",
year = "2020",
booktitle="ACL"
}