Date of Award
Spring 6-2-2023
Document Type
Thesis (Undergraduate)
Department
Computer Science
First Advisor
Soroush Vosoughi
Abstract
This paper describes the AKD team’s system designed for SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS). We implement a simple fine-tuned GPT-3 model, ranking 26 on the leaderboard for task A. We also discuss different approaches to interpretability in the context of critiquing the EDOS task’s sub-category oriented approach. Finally, we propose counterfactual replacement analysis, a novel prototype technique for approaching explainability.
Recommended Citation
Knospe, Anders, "Counterfactual Replacement Analysis for Interpretation of Blackbox Sexism Classification Models" (2023). Computer Science Senior Theses. 19.
https://digitalcommons.dartmouth.edu/cs_senior_theses/19
