Are language models rational? The case of coherence norms and belief revision

The paper titled 'Are language models rational? The case of coherence norms and belief revision' explores the application of rationality norms, specifically coherence norms, to language models. It distinguishes between logical coherence norms and those related to the strength of belief. The authors introduce the Minimal Assent Connection (MAC), a new framework for understanding credence in language models based on internal token probabilities. The findings suggest that while some language models adhere to these rational norms, others do not, raising important questions about AI behavior and safety.