We report a complete sequence-by-sequence landscape of CHSH-form values for six Fibonacci anyons in two encodings, covering all words of length L=3–12 with two generators and L=2–9 with three. In the two-generator d₁ᵦ encoding, braiding alone cannot exceed the classical value: the two generators act on different anyons...
Berkay Yüksel Sayim· Zenodo (CERN European Organi...· 0 citations
We quantify the mutual information I between topological sector labels T and CHSH values S in two-dimensional lattice models. Throughout, I denotes a classical Shannon mutual information between a global discrete label and a scalar measured value; it is not an entanglement entropy between spatial regions. In the Z₂ lat...
Berkay Yüksel Sayim· Zenodo (CERN European Organi...· 0 citations
Abstract (English) This paper presents Synthetic Worldview Reconstruction (SWR)—a method for reconstructing the collective belief systems of sociologically defined groups using large language models. SWR formulates worldview analysis as an inverse problem: given the aggregated public statements and documented actions o...
Lukas Geiger· Zenodo (CERN European Organi...· 0 citations
Software issue resolution task aims to address real-world issues in software repositories based on natural language descriptions provided by users, representing a key aspect of software maintenance. With the rapid development of large language models (LLMs) in reasoning and generative capabilities, LLM-based approaches...
This paper examines whether advanced large language models operating under enhanced deliberative regimes, here termed Reasoning Language Models (RLMs), possess minds under an explicitly defined functional account. We develop an operational definition informed by Newell’s account of cognitive organization and Gärdenfors...
Piotr Świder· Zenodo (CERN European Organi...· 0 citations
Large Language Models (LLMs) have achieved substantial progress in solving complex mathematical problems, yet they often fail to exploit the potential value embedded in their own mistakes. Existing methods either apply coarse-grained corrections or rely on costly self-reflection, overlooking valid reasoning steps and i...
Yuqing Yu, Zihao Li, Lixin Zou et al.· Information Processing & Man...· 0 citations
Research on Artificial Intelligence (AI) and the circular economy (CE) has largely examined how AI can improve circular operations. Much less attention has been paid to AI tools widely used to understand and reason about the CE, particularly large language models (LLMs) such as ChatGPT. Researchers, practitioners, st...
Piero Morseletto, N. Bocken· Journal of Industrial Ecolog...· 0 citations
This paper examines whether advanced large language models operating under enhanced deliberative regimes, here termed Reasoning Language Models (RLMs), possess minds under an explicitly defined functional account. We develop an operational definition informed by Newell’s account of cognitive organization and Gärdenfors...
Piotr Świder· Zenodo (CERN European Organi...· 0 citations
The explicit corrections to the k-omega SST turbulence model presented in the paper Toward non-regressing turbulence closures from large language models: explicit corrections to SST tested on unseen flows (C. Charalampous, submitted to Physics of Fluids), the OpenFOAM v2312 library that evaluates them, the evaluation c...
Charalampos Charalampous· Zenodo (CERN European Organi...· 0 citations
Large Language Models (LLMs) are increasingly used to generate multimodal data for building corpora or simulating synthetic behaviours. A key challenge remains the evaluation of generated data. Comparison with real multimodal human interactions may help address this issue, but unified representations and evaluation fra...
E. Etienne, M. Ochs, J. Loubes et al.· 0 citations
Abstract Large language models generate text token by token, without committing in advance to what a complete answer must contain. This makes them fluent but structurally unreliable: required elements may be omitted, constraints may be ignored, and unsupported claims may appear with unwarranted confidence. Retrieval an...
Wujie Gu· Zenodo (CERN European Organi...· 0 citations
Study summary A frontier large language model (Claude Opus 4.8, model identifier claude-opus-4-8, Anthropic) was tested against the revised Geneva score for pulmonary embolism using simulated patient profiles. Two tasks were run. Task 1, weight elicitation. The model was asked to assign numeric weights to the component...
Thomas F Heston, bo Ryu· Zenodo (CERN European Organi...· 0 citations
