large language models

Regulating Artificial Intelligence and Digital Processes More Widely

Abstract In this chapter, we focus on a digital innovation which is not confined to a single application such as digital platforms, but on one – Artificial Intelligence or AI – which is in course of pervading the whole of the economy and society, and fully deserves the title of one (or several) general purpose technolo...

Large-Language Models as a Cognitive Virus

This work proposes that their diffusion can be understood through a viral analogy, with LLM use spreading through populations, becoming embedded in cognitive and cultural practices, and highlights how LLM adoption may involve nonlinear collective transitions with important consequences for cognitive autonomy.

Emergent Linguistic Grammar from Network Dynamics

This paper investigates the possibility of emergent linguistic grammar arising from the dynamic interactions within a large, interconnected network of agents. The central premise is that complex linguistic structures, traditionally considered the product of human cognitive development, can spontaneously emerge through...

IKH0S - a persistent, multi-vendor world for observing autonomous LLM inhabitants

IKH0S (also written IKHOS) is a persistent, co-evolving digital world inhabited by four large language models drawn from four competing laboratories (Anthropic, OpenAI, xAI and Google). Each model exists as an autonomous inhabitant with lasting memory, prompted once per hour and free to act or to remain silent. The inh...

Thinking Without Words: A Survey of Latent Chain-of-Thought Reasoning in Large Language Models

Large Language Models for Data Augmentation in Product Matching

These are the supplementary materials for the INLG 2026 paper: "Large Language Models for Data Augmentation in Product Matching"Abstract: Large language models (LLMs) are increasingly used for natural language processing tasks in data-scarce domains. In this paper, we study their application to product matching, the ta...

The Particle: Provenance Erasure at Sophistical Refutations 183b34, Measured — Machine-Mediated Reception, Disciplinary Model Collapse, and the World Soul as Degraded Commodity (EA-RECEPTION-PARTICLE-01 v0.2)

Held artifacts — 2 files, served by this archive Fetch, hash, compare. Copying requires no permission and verification requires no trust in this archive. NOTHING-SE34-PARTICLE-APPENDIX-v0.2.md (146,069 bytes) NOTHING-SE34-CHECKLIST.md (1,801 bytes) The Particle: Provenance Erasure at Sophistical Refutations 183b34, Mea...

TestART: Improving LLM-based Unit Test ing via Co-evolution of A utomated Generation and R epair I t eration

Unit testing is crucial for detecting bugs in individual program units but consumes time and effort. Recently, large language models (LLMs) have demonstrated remarkable capabilities in generating unit test cases. However, several problems limit their ability to generate high-quality unit test cases: (1) compilation and...

From search expert to AI steward

Health librarians are already working inside an artificial intelligence (AI) transition. Sometimes the technology is obvious, as in a conversation with a general-purpose large language model (LLM). More often it is embedded in a discovery platform, a systematic review tool, an office suite, a design program or a knowle...

ИСКУССТВЕННЫЙ ИНТЕЛЛЕКТ В КЛИЕНТСКОЙ ПРАКТИКЕ: ВОЗМОЖНОСТИ, ОГРАНИЧЕНИЯ И ЭТИЧЕСКИЕ ГРАНИЦЫ ИСПОЛЬЗОВАНИЯ

Статья посвящена анализу феномена использования больших языковых моделей (ChatGPT и аналогов) клиентами психологической практики для решения личных и эмоциональных проблем. Рассматриваются механизмы, благодаря которым ответы искусственного интеллекта (ИИ) объективно воспроизводят базовые техники психологического консул...

Beyond the Gatekeeper: A Framework for AI-Assisted Open Peer Review and Decentralized Scientific Evaluation

Scientific peer review performs indispensable functions, but it is also a scarce human-attention mechanism operating under increasing submission volume, heterogeneous research communities, uneven access to publishing infrastructure, and persistent concerns about cost, delay, reviewer burden, bias, and reliability. At t...

Annotated Marathi Word Sense Disambiguation Dataset

This dataset is a large-scale sense-annotated resource for Word Sense Disambiguation (WSD) in Marathi, a morphologically rich and relatively low-resource Indic language. It was developed to address the limited availability of reusable, sense-annotated Marathi corpora for supervised WSD research. The final dataset conta...