5 citations · 7 across the 26 of their papers we have counts for
28 papers
Localized, unstable, and entangled: Exploring `Us vs. Them' bias in Large Language Models
Tabia Tanzin Prama, Julia Witte Zimmerman, Christopher M. Danforth +1
Large language models (LLMs) exhibit us-vs.-them bias: A behavioral asymmetry in which prompts framed around an ingroup (``we''/``us'') receive systematically more positive continu…
Self-reported archetypes and behavioral failures in Large Language Models
Tabia Tanzin Prama, Calla Glavin Beauregard, Christopher M. Danforth +1
Every large language model (LLM) has behavioral traits and moral preferences that comprise its character. Whether by design or as an emergent property of training, these systems ex…
Archetypometrics of 'Friends'
Shun Zhang, Tabia Tanzin Prama, Christopher M. Danforth +1
Storytelling inherently revolves around characters. Using the television sitcom `Friends' as a case study, we investigate how well archetype vectors capture both individual charact…
Stop using Media Bias/Fact Check in research
Alejandro Javier Ruiz Iglesias, Julia Witte Zimmerman, Ashley M. A. Fehr +2
Media Bias/Fact Check (MBFC) purports to quantify the bias, credibility, and factuality of reporting for roughly 10,000 media sources, and the resulting data is commonly used in mi…
The queer Hero versus the Fool bias of the queer trait: An archetypometric analysis of the collective portrayal of queerness in fictional stories
Ashley M. A. Fehr, Calla Glavin Beauregard, Julia Witte Zimmerman +4
Visibility in media is pivotal for identity development and for broadening societal views of gender and sexuality. Queer representation has increased in recent years, yet damaging…
Buffy versus Bella: An archetypometric analysis and comparison
Calla Glavin Beauregard, Julia Witte Zimmerman, Ashley M. A. Fehr +6
Fictional stories and characters embody and encode social norms, and their study is a powerful tool through which to understand culture and society. Vampire stories and folklore, i…