AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,173 papers
Abstract / Description: This research note provides the formal mathematical specification and operational framework for the Cloud-Native Blast Radius Analyzer (C-NBRA), a specialized cybersecurity tool designed to continuously map, analyze, and mitigate zero-day breaches in Kubernetes environments using Zero Trust Arch...
In April 2026 a benchmark sent 13 food photographs about 500 times each to four vision-capable large language models (LLMs) at temperature 0.01 and reported median within-photograph coefficients of variation (CV) of 2.4% to 11.0%. Two newer models, Claude Fable 5.1 and GPT-6 Astra, accept no sampling parameter and cann...
The Neurocognitive Threshold Adaptation Map (NTAM) addresses a fundamental question in systems neuroscience: Can two systems that are indistinguishable in the present behave differently because of the histories that produced them? NTAM operationalizes that question through a deterministic computational framework modeli...
Replication package for a study of whether large language models preserve the modal force of requirements when extracting them, whether lightweight uncertainty signals expose strengthening of weak stakeholder intent, and whether output-based checks detect it. Contains the frozen prompts, the benchmark, the campaign con...
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This paper provides the formal mathematical foundation for Boundary 3 of the Instrumentum Vocale verification architecture: the requirement that verification depth must graduate with the falsification degree of the assertion class. It proves that any uniform verification threshold applied to a non-constant falsificatio...
Large Language Models (LLMs) demonstrate strong performance in Natural Language Processing. In neuroanatomy, their response accuracy across hierarchical data structures (responses nested within questions) has not yet been investigated. Evaluating how these models perform under varying cognitive demands is important for...
This working paper develops an integrated forecasting model for the transition of human societies from a scarcity system to an abundance system. Its starting point is that solar electricity follows a stable learning curve and is already the cheapest form of power generation. From near-zero-cost energy the paper derives...
Large Language Models (LLMs) are increasingly used for emotion classification, yet Arabic evaluations remain limited and typically emphasise predictive performance alone. This study presents a deployment-oriented evaluation framework for Arabic emotion classification that complements conventional accuracy-based assessm...
This dataset accompanies the paper "Inferring Gender from Author Names with Local LLMs: A Multi-Model Evaluation" (Journal of Informetrics, 2026). It contains 194,528 first name–country pairs derived from Wikidata, along with gender predictions (Man / Woman / Unknown) produced by 25 open-weight large language models ru...
Critical news reading (CNR), which requires grasping the holistic ideas of and raising critical thoughts on the news, is beneficial yet challenging for general people who usually get information on daily social media. Comments under the news can aid CNR by providing complementary information and other readers’ diverse...
Genomes in artificial evolutionary systems have taken many forms, among them bit strings, program instructions, and network weights, none of which makes the expected behavior apparent to a human being. Can a genome state its behavior directly, in ordinary human language, instead? We ask whether a corpus of natural-lang...
Data and code for a systematic review of the urban climate literature. A large language model extracted structured information from the full text of every paper, and domain experts checked a sample of that extraction. This package lets you check the data and rebuild the paper's statistics, tables and figures. Start her...
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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