1 citations · 1 across the 7 of their papers we have counts for
8 papers
Issue Bias in Generative AI Writing Assistance: Political Issues and LLMs in the Swedish 2026 Election
Bastiaan Bruinsma, Annika Fredén, Paul Röttger +2
Generative AI writing assistants and the Large Language Models (LLMs) that power them are increasingly part of how voters gather information before elections. With growing evidence…
Benchmarking Debiasing Methods for LLM-based Parameter Estimates
Nicolas Audinet de Pieuchon, Adel Daoud, Connor T. Jerzak +2
Large language models (LLMs) offer an inexpensive yet powerful way to annotate text, but are often inconsistent when compared with experts. These errors can bias downstream estimat…
A Knowledge Base for Arts and Inclusion -- The Dataverse data archival platform as a knowledge base management system enabling multimodal accessibility
Moa Johansson, Vyacheslav Tykhonov, Sophia Alexandersson +4
Creating an inclusive art environment requires engaging multiple senses for a fully immersive experience. Culture is inherently synesthetic, enriched by all senses within a shared…
Identifying Non-Replicable Social Science Studies with Language Models
Denitsa Saynova, Kajsa Hansson, Bastiaan Bruinsma +2
In this study, we investigate whether LLMs can be used to indicate if a study in the behavioural social sciences is replicable. Using a dataset of 14 previously replicated studies…
Fact Recall, Heuristics or Pure Guesswork? Precise Interpretations of Language Models for Fact Completion
Denitsa Saynova, Lovisa Hagström, Moa Johansson +2
Language models (LMs) can make a correct prediction based on many possible signals in a prompt, not all corresponding to recall of factual associations. However, current interpreta…
Setting the AI Agenda -- Evidence from Sweden in the ChatGPT Era
Bastiaan Bruinsma, Annika Fredén, Kajsa Hansson +3
This paper examines the development of the Artificial Intelligence (AI) meta-debate in Sweden before and after the release of ChatGPT. From the perspective of agenda-setting theory…
Can Large Language Models (or Humans) Disentangle Text?
Nicolas Audinet de Pieuchon, Adel Daoud, Connor Thomas Jerzak +2
We investigate the potential of large language models (LLMs) to disentangle text variables--to remove the textual traces of an undesired forbidden variable in a task sometimes know…
The Effect of Scaling, Retrieval Augmentation and Form on the Factual Consistency of Language Models
Lovisa Hagström, Denitsa Saynova, Tobias Norlund +2
Large Language Models (LLMs) make natural interfaces to factual knowledge, but their usefulness is limited by their tendency to deliver inconsistent answers to semantically equival…