Improving the Interpretability of Neural Sentiment Classifiers via Data Augmentation

By Hanjie Chen, Hanjie Chen, Yangfeng Ji. 2019

7 citations recorded by the source corpus.

Subfields: Natural Language Processing, Safety, Robustness & Interpretability

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

1. Willem H. Zuidema
2. Samira Abnar
3. Yonatan Belinkov
4. Dieuwke Hupkes
5. Yoav Goldberg
6. John Hewitt
7. Tal Linzen
8. James R. Glass

In Safety, Robustness & Interpretability

1. Willem H. Zuidema
2. Samira Abnar
3. Yonatan Belinkov
4. Dieuwke Hupkes

Citations in the corpus

• Quantifying Attention Flow in Transformers (2020, background): “…the easiest and most popular approach to interpret a model’s decisions and to gain insights about its internals (Vaswani et al., 2017; Xu et al., 2015; Wang et al., 2016; Lee et al., 2017; Dehghani et al., 2019; Rockt¨aschel et al., 2016; Chen and Ji, 2019; Coenen et al., 2019; Clark et al., 2019).”