Evaluating Language Model Character Traits

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Ward, Francis Rhys, Yang, Zejia, Jackson, Alex, Brown, Randy, Smith, Chandler, Colverd, Grace, Thomson, Louis, Douglas, Raymond, Bartak, Patrik, Rowan, Andrew
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866917795793469440
author Ward, Francis Rhys
Yang, Zejia
Jackson, Alex
Brown, Randy
Smith, Chandler
Colverd, Grace
Thomson, Louis
Douglas, Raymond
Bartak, Patrik
Rowan, Andrew
author_facet Ward, Francis Rhys
Yang, Zejia
Jackson, Alex
Brown, Randy
Smith, Chandler
Colverd, Grace
Thomson, Louis
Douglas, Raymond
Bartak, Patrik
Rowan, Andrew
contents Language models (LMs) can exhibit human-like behaviour, but it is unclear how to describe this behaviour without undue anthropomorphism. We formalise a behaviourist view of LM character traits: qualities such as truthfulness, sycophancy, or coherent beliefs and intentions, which may manifest as consistent patterns of behaviour. Our theory is grounded in empirical demonstrations of LMs exhibiting different character traits, such as accurate and logically coherent beliefs, and helpful and harmless intentions. We find that the consistency with which LMs exhibit certain character traits varies with model size, fine-tuning, and prompting. In addition to characterising LM character traits, we evaluate how these traits develop over the course of an interaction. We find that traits such as truthfulness and harmfulness can be stationary, i.e., consistent over an interaction, in certain contexts, but may be reflective in different contexts, meaning they mirror the LM's behavior in the preceding interaction. Our formalism enables us to describe LM behaviour precisely in intuitive language, without undue anthropomorphism.
format Preprint
id arxiv_https___arxiv_org_abs_2410_04272
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Evaluating Language Model Character Traits
Ward, Francis Rhys
Yang, Zejia
Jackson, Alex
Brown, Randy
Smith, Chandler
Colverd, Grace
Thomson, Louis
Douglas, Raymond
Bartak, Patrik
Rowan, Andrew
Computation and Language
Language models (LMs) can exhibit human-like behaviour, but it is unclear how to describe this behaviour without undue anthropomorphism. We formalise a behaviourist view of LM character traits: qualities such as truthfulness, sycophancy, or coherent beliefs and intentions, which may manifest as consistent patterns of behaviour. Our theory is grounded in empirical demonstrations of LMs exhibiting different character traits, such as accurate and logically coherent beliefs, and helpful and harmless intentions. We find that the consistency with which LMs exhibit certain character traits varies with model size, fine-tuning, and prompting. In addition to characterising LM character traits, we evaluate how these traits develop over the course of an interaction. We find that traits such as truthfulness and harmfulness can be stationary, i.e., consistent over an interaction, in certain contexts, but may be reflective in different contexts, meaning they mirror the LM's behavior in the preceding interaction. Our formalism enables us to describe LM behaviour precisely in intuitive language, without undue anthropomorphism.
title Evaluating Language Model Character Traits
topic Computation and Language
url https://arxiv.org/abs/2410.04272