Measuring Psychological Depth in Language Models
Fabrice Y. Harel-Canada, Hanyu Zhou, Sreya Muppalla, Zeynep Senahan Yildiz, Miryung Kim, Amit Sahai, and Nanyun Peng, in Proceedings of The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
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Abstract
This paper introduces the Psychological Depth Scale (PDS), measuring the ability of LLMs to produce emotionally engaging stories. We validate our framework and explore automation techniques for scaling analyses.
Bib Entry
@inproceedings{harel2024measuring,
author = {Harel-Canada, Fabrice Y and Zhou, Hanyu and Muppalla, Sreya and Yildiz, Zeynep Senahan and Kim, Miryung and Sahai, Amit and Peng, Nanyun},
title = {Measuring Psychological Depth in Language Models},
booktitle = {Proceedings of The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
year = {2024}
}