Word Embedding Attention Network

Code for "Word Embedding Attention Network: Generating Words by Querying Distributed Word Representations for Paraphrase Generation" [pdf]

Requirements

• Ubuntu 16.04
• Python 3.5
• Pytorch 0.2.0
• ROUGE

Data

• LCSTS
• PWKP
• EWSEW

Run

python3 preprocess.py -train_src TRAIN_SRC_DATA -train_tgt TRAIN_TGT_DATA
		      -test_src TEST_SRC_DATA -test_tgt TEST_TGT_DATA
		      -valid_src VALID_SRC_DATA -valid_tgt VALID_TGT_DATA
		      -save_data data/lcsts/lcsts.low.share.train.pt
		      -lower -share

python3 train.py -gpus 0 -score general -config lcsts.yaml -log wean

python3 predict.py -gpus 0 -score general -config lcsts.yaml -unk -restore data/lcsts/wean/best_rouge_checkpoint.pt

Cite

To use this code, please cite the following paper:

Shuming Ma, Xu Sun, Wei Li, Sujian Li, Wenjie Li, and Xuancheng Ren. Word Embedding Attention Network: Generating Words by Querying Distributed Word Representations for Paraphrase Generation. In proceedings of NAACL-HLT 2018.

bibtext:

@inproceedings{wean,
  author    = {Shuming Ma and Xu Sun and Wei Li and Sujian Li and Wenjie Li and Xuancheng Ren},
  title     = {Word Embedding Attention Network: Generating Words by Querying Distributed Word 
	       Representations for Paraphrase Generation},
  booktitle = {{NAACL} {HLT} 2018, The 2018 Conference of the North American Chapter
	       of the Association for Computational Linguistics: Human Language Technologies},
  year      = {2018}
}