L1-Refinement

Code for Cross-Lingual Word Embedding Refinement by ℓ1 Norm Optimisation

Tested environment

• python==3.7.6
• faiss==1.6.3
• scipy==1.4.1
• numpy==1.18.1
• torch==1.6.0
• fastText==0.9.2
• Intel Core i9-9900K CPU with 32GB Memory

Example command

python refiner.py --src_lang en --tgt_lang de --src_emb aligned/en-de/embeddings/en.vec --tgt_emb aligned/en-de/embeddings/de.vec --exp_path a/target/dir

About

If you like our project or find it useful, please give us a ⭐ and cite us

@inproceedings{L1-Refinement,
    title = "Cross-Lingual Word Embedding Refinement by $\ell_{1}$ Norm Optimisation",
    author = "Peng, Xutan  and
      Lin, Chenghua  and
      Stevenson, Mark",
    booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
    month = jun,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2021.naacl-main.214",
    pages = "2690--2701"
}

This code is based on MUSE