Selecting Shots for Demographic Fairness in Few-Shot Learning with Large Language Models
Published in NLP for Positive Impact, 2023
Recommended citation: Selecting Shots for Demographic Fairness in Few-Shot Learning with Large Language Models. C Aguirre, K Sasse, I Cachola, M Dredze - Third Workshop on NLP for Positive Impact @ EMNLP 2024, 2024. https://aclanthology.org/2024.nlp4pi-1.4/
In this work, we explore the effect of shots, which directly affect the performance of models, on the fairness of LLMs as NLP classification systems. We consider how different shot selection strategies, both existing and new demographically sensitive methods, affect model fairness across three standard fairness datasets. We discuss how future work can include LLM fairness evaluations.
Recommended citation: Selecting Shots for Demographic Fairness in Few-Shot Learning with Large Language Models. C Aguirre, K Sasse, I Cachola, M Dredze Third Workshop on NLP for Positive Impact @ EMNLP 2024, 2024.