47 citations · 49 across the 2 of their papers we have counts for
4 papers
ContextAdapt: Evaluating Contextual Adaptation and Value Alignment in LLMs
Olivia Macmillan-Scott, Mirco Musolesi
Values such as honesty, autonomy, and confidentiality are often regarded as general principles underpinning AI alignment. However, what it means to act in accordance with these val…
Framing the Narrative: Ideological Mimicry in Large Language Models
Olivia Macmillan-Scott, Michael Jacobs, Nils Metternich +1
Large language models (LLMs) are increasingly used to answer questions about politically contentious issues, yet evaluations typically treat a model's stance as a relatively stable…
(Ir)rationality and Cognitive Biases in Large Language Models
Olivia Macmillan-Scott, Mirco Musolesi
Do large language models (LLMs) display rational reasoning? LLMs have been shown to contain human biases due to the data they have been trained on; whether this is reflected in rat…
(Ir)rationality in AI: State of the Art, Research Challenges and Open Questions
Olivia Macmillan-Scott, Mirco Musolesi
The concept of rationality is central to the field of artificial intelligence (AI). Whether we are seeking to simulate human reasoning, or trying to achieve bounded optimality, our…