We investigate the benefits of CAD for social NLP models by focusing on three social computing constructs — sentiment, sexism, and hate speech ...

Sep 14, 2021 · We investigate the benefits of CAD for social NLP models by focusing on three social computing constructs -- sentiment, sexism, and hate speech.

Sep 10, 2024 · We investigate the benefits of CAD for social NLP models by focusing on three social computing constructs -- sentiment, sexism, and hate speech.

Therefore, when counterfactuals block spurious correlations, they may not help the model in terms of accuracy and could even have a counterproductive effect ( ...

How Does Counterfactually Augmented Data Impact Models for Social Computing Constructs? Sen, Indira (Corresponding author); Samory, Mattia; Flöck, Fabian; ...

Nov 8, 2021 · Hi Mieradilijiang, thanks for the questions! All the counterfactuals were generated by human annotators who made minimal edits to existing ...

How Does Counterfactually Augmented Data Impact Models for Social Computing Constructs? Powered by the Academic theme for Hugo. Cite. ×. Copy Download.

Feb 13, 2024 · Our results show that augmenting training data of smaller models with LLM gen- erated CFs consistently improves generalization capabilities of ...

This repository contains the code for the EMNLP'21 paper, 'How Does Counterfactually Augmented Data Impact Models for Social Computing Constructs?' and the ...

Sep 17, 2021 · "How Does Counterfactually Augmented Data Impact Models for Social Computing Constructs?" analyses reasons CAD is beneficial for social NLP ...