Vsl
Code for "Variational Sequential Labelers for Semi-Supervised Learning" (EMNLP 2018)
Install / Use
/learn @mingdachen/VslREADME
VSL
A PyTorch implementation of "Variational Sequential Labelers for Semi-Supervised Learning" (EMNLP 2018)
Prerequisites
- Python 3.5
- PyTorch 0.3.0
- Scikit-Learn
- NumPy
Data and Pretrained Embeddings
Download: Twitter, Universal Dependencies, Embeddings (for Twitter and UD)
Run process_{ner,twitter,ud}_data.py first to generate *.pkl files and then use it as input for vsl_{g,gg}.py.
Citation
@inproceedings{mchen-variational-18,
author = {Mingda Chen and Qingming Tang and Karen Livescu and Kevin Gimpel},
title = {Variational Sequential Labelers for Semi-Supervised Learning},
booktitle = {Proc. of {EMNLP}},
year = {2018}
}
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