AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,329 papers
EuLLM is an open-source platform for creating, distributing, and running sovereign EU-compliant Large Language Models, designed for verticalization across domains, languages, and brands while ensuring AI Act compliance. The platform consists of three components: Engine — a Rust-based inference runtime built on top of l...
Carbon capture and storage (CCS) is recognized as an important technology for reducing greenhouse gas emissions and achieving climate targets, yet some segments of society express public opposition. Public opposition, even when expressed by minority groups, has at times influenced CCS project outcomes. Opposition exten...
Recent advances in large language models (LLMs) have enabled artificial systems to generate responses widely perceived as empathic, raising fundamental questions about the nature and value of empathy. This chapter examines why, despite evidence that AI can equal or even surpass humans in tasks of cognitive empathy, hum...
A language model trained on nothing published after 1938, asked what year it is, answers 1899. Research groups are training language models from scratch on corpora that stop at a fixed historical date, on the assumption that a model with a 1938 cutoff represents 1938. This work measures that assumption and finds it wro...
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中文摘要 定子‑动子宇宙模型(Stator‑Rotor Cosmic Model, SRCM‑v1.4)是一套基于离散时空的猜想性统一物理框架。该模型引入两类本体单元:静态不可再分的空间格点定子与作为能量最小单元的动态动子;空间采用菱形十二面体密堆积(面心立方晶格),时间由普朗克时长的离散帧构成。模型设置九条基础公理,通过定子势函数 Φₛ、动子簇函数 Ψᵣ、全局同步约束...
As psychological science is shifting from traditional null-hypothesis significance testing toward interval-based hypothesis testing, researchers have to determine and justify what the smallest effect size is that matters practically or theoretically, also known as the smallest effect size of interest (SESOI). However,...
Universal writing screening requires scoring approaches that are feasible and supported by validity evidence. This study evaluated large language model (LLM)-based comparative judgment (CJ) for scoring informational writing assessments completed by 1,208 students in Grades 3–6 across three screening occasions. Seven LL...
In recent years, cybersecurity threats have increasingly exploited human behaviour rather than purely technical vulnerabilities, exposing the limits of traditional awareness programmes delivered outside real-world contexts. To bridge this gap, we introduce TrainShield, an interaction paradigm for contextual cybersecuri...
Reproduction materials for a study of Legal Judgment Prediction (LJP) on Korean drunk-driving cases: an attorney-verified benchmark of 1,500 cases drawn from the LBox Open corpus, eight classical machine-learning configurations, four large-language-model configurations, and a comparison of the two model families on bot...
High quality data on natural hazard damages are crucial for effective disaster risk management. Yet, existing impact datasets remain limited and often biased toward Northern countries and monetary losses. To help address these gaps, we present ROUGE (Redcross Operations Unified Global Emergency database); a new socio...
This paper develops a dynamic framework for analyzing civilizational reorganization by extending the theory of reaction synchronization along a temporal axis. Rather than treating civilizations as unified entities that rise, decline, and replace one another, it conceptualizes civilization as an overlapping assemblage o...
EuLLM is an open-source platform for creating, distributing, and running sovereign EU-compliant Large Language Models, designed for verticalization across domains, languages, and brands while ensuring AI Act compliance. The platform consists of three components: Engine — a Rust-based inference runtime built on top of l...
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.
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