A new preprint sets out a framework for describing when a learned or acquired representation broadens what a system can do, and where that broadening stops. Its central claim is that a system can gain new cognitive capabilities from a representation without inheriting the abilities that were used to create it. The work aims to make the scope and limits of such capability gains specifiable.
A new arXiv paper examines the role of language in multimodal systems, noting that language models use text as input, output, and an increasingly internal representation. The author argues that whether language should hold all of these positions depends on what language does to the system that relies on it, drawing on evidence from human perception and cognition.
A new preprint argues that the link between large brains and variable environments does not necessarily mean those brains evolved under such conditions. The author suggests big brains may instead develop in stable settings and only later enable species to move into new or changing habitats. This reframes the Cognitive Buffer Hypothesis as a possible consequence rather than a cause.
A new arXiv paper draws on third-wave Extended Mind theory and radical enactivism to argue against models that treat cognition as manipulation of internal representations. The authors introduce an ABC framework in which translation is framed as an enacted process of the translating mind rather than symbolic computation. The work appears in the computation and language category as a revised version.
A preprint on arXiv examines the role of chatbots as conversational partners in problem-solving exchanges, asking where their capabilities end. The author draws on ideas from aggregation dynamics, cognitive linguistics, neuropsychology and psychology to frame the analysis. It is a conceptual discussion rather than an experimental study or product announcement.
An arXiv paper in cs.AI introduces a metric framework for telling apart AI systems that genuinely boost human reasoning from those that encourage users to offload their thinking. The authors note that the line between cognitive amplification and cognitive delegation has been poorly defined, and they propose measurable criteria to close that gap. The work may help researchers and product teams evaluate how AI-assisted decision tools affect human cognition.