Understanding The Effect Of Temperature On Alignment With Human Opinions

Fuente: arXiv
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Main Authors: Pavlovic, Maja, Poesio, Massimo
Format: Preprint
Published: 2024
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author Pavlovic, Maja
Poesio, Massimo
author_facet Pavlovic, Maja
Poesio, Massimo
contents With the increasing capabilities of LLMs, recent studies focus on understanding whose opinions are represented by them and how to effectively extract aligned opinion distributions. We conducted an empirical analysis of three straightforward methods for obtaining distributions and evaluated the results across a variety of metrics. Our findings suggest that sampling and log-probability approaches with simple parameter adjustments can return better aligned outputs in subjective tasks compared to direct prompting. Yet, assuming models reflect human opinions may be limiting, highlighting the need for further research on how human subjectivity affects model uncertainty.
format Preprint
id arxiv_https___arxiv_org_abs_2411_10080
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Understanding The Effect Of Temperature On Alignment With Human Opinions
Pavlovic, Maja
Poesio, Massimo
Computation and Language
Computers and Society
With the increasing capabilities of LLMs, recent studies focus on understanding whose opinions are represented by them and how to effectively extract aligned opinion distributions. We conducted an empirical analysis of three straightforward methods for obtaining distributions and evaluated the results across a variety of metrics. Our findings suggest that sampling and log-probability approaches with simple parameter adjustments can return better aligned outputs in subjective tasks compared to direct prompting. Yet, assuming models reflect human opinions may be limiting, highlighting the need for further research on how human subjectivity affects model uncertainty.
title Understanding The Effect Of Temperature On Alignment With Human Opinions
topic Computation and Language
Computers and Society
url https://arxiv.org/abs/2411.10080