6 citations · 6 across the 4 of their papers we have counts for
5 papers
Political Sorting Can Drive AI Models Apart Through User Feedback
Petter Törnberg, Michael Heseltine, Nicolò Pagan +3
Large language models are rapidly becoming an important source of political information. This raises a fundamental question: will AI systems support a shared basis for political kn…
Polarization by Default: Auditing Recommendation Bias in LLM-Based Content Curation
Nicolò Pagan, Christopher Barrie, Chris Andrew Bail +1
Large Language Models (LLMs) are increasingly deployed to curate and rank human-created content, yet the nature and structure of their biases in these tasks remains poorly understo…
Computational Turing Test Reveals Systematic Differences Between Human and AI Language
Nicolò Pagan, Petter Törnberg, Christopher A. Bail +2
Large language models (LLMs) are increasingly used in the social sciences to simulate human behavior, based on the assumption that they can generate realistic, human-like text. Yet…
Emergent LLM behaviors are observationally equivalent to data leakage
Christopher Barrie, Petter Törnberg
Ashery et al. recently argue that large language models (LLMs), when paired to play a classic "naming game," spontaneously develop linguistic conventions reminiscent of human socia…
Prompt Stability Scoring for Text Annotation with Large Language Models
Christopher Barrie, Elli Palaiologou, Petter Törnberg
Researchers are increasingly using language models (LMs) for text annotation. These approaches rely only on a prompt telling the model to return a given output according to a set o…