@inproceedings{65460317597446209737a3e80db2f98f,
title = "Retrieval Augmented Generation of Subjective Explanations for Socioeconomic Scenarios",
abstract = "We introduce a novel retrieval augmented generation approach that explicitly models causality and subjectivity. We use it to generate explanations for socioeconomic scenarios that capture beliefs of local populations. Through intrinsic and extrinsic evaluation, we show that our explanations, contextualized using causal and subjective information retrieved from local news sources, are rated higher than those produced by other large language models both in terms of mimicking the real population and the explanations quality. We also provide a discussion of the role subjectivity plays in evaluation of this natural language generation task.",
author = "Dumitru, \{Razvan Gabriel\} and Maria Alexeeva and Keith Alcock and Nargiza Ludgate and Cheonkam Jeong and Abdurahaman, \{Zara Fatima\} and Prateek Puri and Brian Kirchhoff and Santadarshan Sadhu and Mihai Surdeanu",
note = "Publisher Copyright: {\textcopyright} 2024 Association for Computational Linguistics.; 6thWorkshop on Natural Language Processing and Computational Social Science, NLP+CSS 2024 ; Conference date: 21-06-2024",
year = "2024",
language = "English (US)",
series = "NLP+CSS 2024 - 6thWorkshop on Natural Language Processing and Computational Social Science, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "68--85",
editor = "Dallas Card and Anjalie Field and Dirk Hovy and Katherine Keith",
booktitle = "NLP+CSS 2024 - 6thWorkshop on Natural Language Processing and Computational Social Science, Proceedings of the Workshop",
}