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Paper, code, data, and supplementary material for our paper "On the Softmax Bottleneck of Recurrent Language Models", which got accepted at the main track of AAAI 2021.

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pdfs directory

It contains the pdfs of the paper, supplementary material, reviews, author response, and meta review.

Note

  • Most of the code is from the open sourced implementation of AWD-LSTM and MoS.
  • base_models contain the bottom layers of the AWD-LSTM network that are common to all models under comparison.
  • the differences for Softmax, SS, GSS, LMS-PLIF, MoS, and MoC models are grouped accordingly in top_models.
  • main.py is the file to lookout for model training and evaluation.
  • analysis.py has the code for most of the analysis that we had presented in our paper.
  • To make the code work, replace the strings "<your_X>" to the right values. X could be any substring. Search them accordingly. We replaced some of the strings with such values to preserve anonymity.

More information

If you are curious or still looking for more information, please look at my master's thesis.

TODO

  • Add all the required attributions
  • Docs about the code
  • Link the paper

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Paper, code, data, and supplementary material for our paper "On the Softmax Bottleneck of Recurrent Language Models", which got accepted at the main track of AAAI 2021.

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