AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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3,200 papers
After 536 commits, I am incredibly proud to announce the first stable release of MOP Simulator V3.7! 🚀 This release evolves the project from a standalone native binary into a full-stack autonomous AI research platform. It tightly couples a high-performance C++23 terminal ballistics simulation engine with a Node.js/Exp...
lctriage (released as "Atlas Robuste" in version 1.0) is a reproducible pipeline for extracting features from photometric time series, ranking targets by atypicality, and measuring whether that ranking can be trusted. This version accompanies the paper Persistence, Not Consensus: Measured Triage of Unsupervised Anomaly...
This Zenodo record contains the processed data and trained models supporting the manuscript “Machine Learning Reconstruction of Glider Dissolved Oxygen: Accuracy Across Missions, Depths, and Years.” The files support the model evaluations, dissolved oxygen reconstructions, interannual analyses, and numerical results re...
Replication package associated with the scientific article: "Anticipatory Test Oracles for Prompt Prioritization in LLM Toxicity Testing", submitted for possible publication to the 49th International Conference on Software Engineering (ICSE 2027). The package contains the implementation of Anticipatory Toxicity Oracles...
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This release synchronizes the Americas Great Resorts canonical reference repository through September 24, 2026. Key updates: Expands the repository to 170 Markdown files and 157 content records. Adds the corpus twin for "AI Visibility Is Becoming Software. The Harder Problem Is Knowledge Formation." Adds and updates KF...
This dataset and code package accompanies the study of foundation machine-learning interatomic potentials (MLIPs) for vacancy-anchored hydrogen migration in pyrite, marcasite, mackinawite and greigite. Foundation MLIPs offer inexpensive migration-barrier calculations, but their reliability for hydrogen defects in magne...
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22955348. Reviewers: Diptarup Mallick, Hala Taha Elbashir, Lukman Boyi Adamu,Prerna Mehta, Shubham Kalamkar, Joseph Odunayo Igbokwe, Egide KAYIRANGA, Deepak Vitthal Sawant, Suhagiya...
This work presents a deployed vision–language decision-support platform for tomato harvest that connects image capture, identity verification, ripeness grading, harvest guidance, yield estimation, damage assessment, weather-conditioned loss projection, multilingual reporting, and persistent provenance within a single a...
This work presents a deployed vision–language decision-support platform for tomato harvest that connects image capture, identity verification, ripeness grading, harvest guidance, yield estimation, damage assessment, weather-conditioned loss projection, multilingual reporting, and persistent provenance within a single a...
In this article, we propose a rapid junction temperature (<inline-formula> <tex-math notation="LaTeX">$T_{\mathrm {j}}$ </tex-math></inline-formula>) calculation method for SiC power modules using third harmonic injection pulsewidth modulation (Thi-PWM) control, which is particularly useful for transient <inline-formul...
Investigating the real-world impact of GitHub Copilot on software engineering, this field study uncovers a critical disconnect between gains in individual developer efficiency and improvements in organizational throughput. Using a multi-method approach, we employed the Organizational Ohm’s Law framework and integrated...
Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. The post From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence appeared first on Microsoft Research.
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
A Blog post by IBM Granite on Hugging Face
“X-Hinges” helps design and 3D print items like lamps and gloves with an interactive twist: automatically embedded sensors that perceive and adaptively respond to human contact.
We’re giving developers, enterprises, scientists, and consumers access to Gemini 4 Argon, our latest frontier model.
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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