3 papers
cs.CL2026
Mechanistic Indicators of Understanding in Large Language Models
Pierre Beckmann, Matthieu Queloz
Large language models (LLMs) are often portrayed as merely imitating linguistic patterns without genuine understanding. We argue that recent findings in mechanistic interpretabilit…
cs.AI2025
Explainability Through Systematicity: The Hard Systematicity Challenge for Artificial Intelligence
Matthieu Queloz
This paper argues that explainability is only one facet of a broader ideal that shapes our expectations towards artificial intelligence (AI). Fundamentally, the issue is to what ex…
cs.CY2025
Can AI Rely on the Systematicity of Truth? The Challenge of Modelling Normative Domains
Matthieu Queloz
A key assumption fuelling optimism about the progress of large language models (LLMs) in accurately and comprehensively modelling the world is that the truth is systematic: true st…