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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 (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...
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...
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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...
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...
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...
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...
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...
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...
Shared accommodation in historic districts enriches tourists' local cultural experiences and supports urban regeneration. However, how objective spatial conditions are perceived and associated with satisfaction remains insufficiently explained. This study examines historic-district shared accommodation through a two-st...
A large language model (LLM) running inside an industrial instrument will fail on some of what the operator asks. Whether such a failure is justified as evidence of a capability deficit of the model, or only of a burden the instrument left at its evidence interface, is not answerable from an accuracy score, and a deplo...
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
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