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 continuations than matched prompts framed around an outgroup (``they''/``them''). Using Edge Attribution Patching (EAP), we localize this behavior...
Tabia Tanzin Prama, J. Zimmerman, C. Danforth et al.· 0 citations
A wearable illness signature is robust within individuals and reproducible at population scale, and simple aggregate temperature monitoring may be sufficient for campus health surveillance.
B. Loftness, S. Rosenblatt, J. Hidalgo et al.· medRxiv· 0 citations
This work map the self-reported personality archetypes of 22 LLMs spanning closed-source frontier systems and open-source models, providing a reproducible, character-grounded framework for evaluating what LLMs are, not just what they do.
Tabia Tanzin Prama, C. Beauregard, C. Danforth et al.· 0 citations
Storytelling inherently revolves around characters. Using the television sitcom `Friends'as a case study, we investigate how well archetype vectors capture both individual characterization and the relational structure of a specific ensemble. Our work is based on the archetypometrics framework, which locates 2,000 ficti...
Shunyou Zhang, Tabia Tanzin Prama, C. M. Danforth et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
