@inproceedings{zhang-etal-2016-libn3l,
    title = "{L}ib{N}3{L}:A Lightweight Package for Neural {NLP}",
    author = "Zhang, Meishan  and
      Yang, Jie  and
      Teng, Zhiyang  and
      Zhang, Yue",
    booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC} 2016)",
    month = may,
    year = "2016",
    address = "Portoro{\v{z}}, Slovenia",
    publisher = "European Language Resources Association (ELRA)",
    url = "https://www.aclweb.org/anthology/L16-1034",
    pages = "225--229",
    abstract = "We present a light-weight machine learning tool for NLP research. The package supports operations on both discrete and dense vectors, facilitating implementation of linear models as well as neural models. It provides several basic layers which mainly aims for single-layer linear and non-linear transformations. By using these layers, we can conveniently implement linear models and simple neural models. Besides, this package also integrates several complex layers by composing those basic layers, such as RNN, Attention Pooling, LSTM and gated RNN. Those complex layers can be used to implement deep neural models directly.",
}