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Analysis Methods in Neural NLP

This site contains the accompanying supplementary materials for the paper "Analysis Methods in Neural Language Processing: A Survey", TACL 2019, available here.

Tables

• Table SM1: A categorization of work trying to find linguistic information in neural networks according to the neural network component investigated, the linguistic property sought, and the analysis method. See Section 2 in the paper.
• Table SM2: A categorization of challenge sets for evaluating neural networks according to the NLP task, the linguistic phenomena, the represented languages, the dataset size, and the construction method. See Section 4 in the paper.
• Table SM3: A categorization of methods for adversarial examples in NLP according to adversary's knowledge (white-box vs. black-box), attack specificity (targeted vs. non-targeted), the modified linguistic unit (words, characters, etc.), and the attacked task. See Section 5 in the paper.

References

The list of references is available here.

Contributions

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Citation

If you find this resource useful, please cite our paper:

@Article{belinkov:2019:tacl,
  author    = {Belinkov, Yonatan  and  Glass, James},
  title     = {Analysis Methods in Neural Language Processing: A Survey},
  journal = {Transactions of the Association for Computational Linguistics (TACL)},
  year      = {2019},
  volume    = {7},
  pages     = {49--72},
  doi       = {10.1162/tacl\_a\_00254}
}