LibN3L:A Lightweight Package for Neural NLP

Meishan Zhang, Jie Yang, Zhiyang Teng, Yue Zhang


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.
Anthology ID:
L16-1034
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
225–229
Language:
URL:
https://aclanthology.org/L16-1034
DOI:
Bibkey:
Cite (ACL):
Meishan Zhang, Jie Yang, Zhiyang Teng, and Yue Zhang. 2016. LibN3L:A Lightweight Package for Neural NLP. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 225–229, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
LibN3L:A Lightweight Package for Neural NLP (Zhang et al., LREC 2016)
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PDF:
https://aclanthology.org/L16-1034.pdf