AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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3,351 papers
Memoria.ia v1.0.0-rc1 — Release Candidate 1 Release date: 2026-08-30 Summary v1.0.0-rc1 is the first publication candidate for the Memoria.ia v1 line. It consolidates the validated Resolutive Memory research lineage with the deployable PC/server product layer and the native/mobile runtime path, while keeping post-v1 ex...
Artifact for the paper “FitGen: Validation and Guided Repair of LLM Generated Executable Fitness Functions for Search Based Software Testing,” published in the Proceedings of the 7th International Workshop on Automated Program Repair (APR '26), co-located with ASE 2026. This artifact contains the source code, benchmark...
This record contains the simulated Zernike-coefficient datasets, source code, model configurations, pretrained weights, and machine-readable numerical results supporting the SI-Mamba study. The archived learning models are LSTM, Mamba, and SI-Mamba. It includes the training set, five held-out test sets, 25 boundary-con...
Your AI can say the test passed. Code Factory asks whether the test could ever have failed. Solo developers start with one local proof; teams bind the real diff, intent, independent checks, and receipts instead of trusting an agent's narrative. Version 0.45.1 adds a deterministic AppForge App Review evidence gate: 30 p...
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Sparse departures from independence in two-way tables: a heteroscedasticity profile and detection boundary, an adaptive higher-criticism gate, and an assumption-lean exact anchor William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Co...
RiboGRAM Archives This release contains the source code, model checkpoints, benchmark datasets, and example outputs for the study RiboGRAM learns multi-scale non-coding RNA grammar for structural and regulatory inference. RiboGRAM is a self-supervised RNA representation model for learning multi-scale and position-resol...
Retained-State Middleware for Governed Selection defines a software category concerned with how retained history is allowed to influence selection among actions that a host system has already declared permissible. The central principle is: retained history is eligible evidence, not automatic authority. This technical n...
This record contains the locked confirmatory scientific results of HLV-R-MECH-001, a prospectively frozen mechanism test of the previously observed degree-preserving rewire spectral residual within the Helix–Light–Vortex Framework (HLV), positioned as a Cut-and-Project and Incidence-Spectral Research Programme. The con...
This record contains the simulated Zernike-coefficient datasets, source code, model configurations, pretrained weights, and machine-readable numerical results supporting the SI-Mamba study. The archived learning models are LSTM, Mamba, and SI-Mamba. It includes the training set, five held-out test sets, 25 boundary-con...
This archive contains the modular ICD-10-CM registry implementation, unit tests, and de-identified software vignette artifacts associated with the CMPB manuscript: 'A typed ICD-10-CM registry for constrained differential-diagnosis pools in clinical decision support'. Contents: icd_registry.py ICD-10-CM diagnosis regist...
Persistent cognition changes the assurance requirements of AI coding agents because durable memories, lessons, reusable skills, structural observations, and derived knowledge can influence later engineering work after repository state, task context, or execution sessions have changed. C2Cognitive Core v1.0.0 presents a...
This archive contains the modular ICD-10-CM registry implementation, unit tests, and de-identified software vignette artifacts associated with the CMPB manuscript: 'A typed ICD-10-CM registry for constrained differential-diagnosis pools in clinical decision support'. Contents: icd_registry.py ICD-10-CM diagnosis regist...
AI agents can generate code at a scale that’s hard for humans to review line-by-line. PDD Kit helps ensure the code is doing what the developer intended by creating formal specifications and testing against them. It converts developer intent into a Verus specification, proves AI-generated code meets it for every input, and uses tests where proofs aren't practical. Developers review intent, not every line. The post Formally verifying agent-written full-stack web apps with PDD Kit appeared first o…
A Blog post by Ai2 on Hugging Face
GPT-Lab
· gpt-lab.eu
Nov 3, 2026
Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.
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
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