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Convolutional RNN

Implementation based on [1].


Run ./ to fetch the data. The project structure should now look like this:

├── conv_rnn/
│   ├── data/
│   ├── saves/
│   └── *.*

You may then run python and python for training and testing, respectively. For more options, add the -h switch.

Empirical results

Best dev Test
48.1 48.9


[1] Chenglong Wang, Feijun Jiang, and Hongxia Yang. 2017. A Hybrid Framework for Text Modeling with Convolutional RNN. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '17).

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