AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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3,243 papers
AI-enabled interventions show promise as adjuncts to ophthalmology training, particularly for diagnostic learning and objective feedback, but evidence remains limited by small samples and heterogeneity, requiring larger, standardized studies to define AI's role.
A strategic game arena is introduced that situates LLM agents in social deduction scenarios inspired by Among Us, requiring theory of mind, deception detection, and cooperative deliberation under uncertainty, and motivates architectural changes for virtual agents that must cooperate with humans.
This revised manuscript presents a controlled study of morphological hijacking in frozen language-model representations using the synthetic LUXVAR/VARZIN framework. The study shows that adversarial surface structure can dominate frozen representations, while a lightweight trained projection head can substantially recov...
Background. RewardBench 2 aggregates pairwise preference accuracy across heterogeneous task families (factuality, instruction following, safety, and others). A single leaderboard score can mask systematic subset specialization, yet standard benchmark reporting rarely tests whether accuracy is independent of task catego...
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The Spanish PEAS shows robust evidence for a three-dimensional structure, good reliability, and measurement invariance up to thresholds across age groups in Chilean adults.
DOI: 10.5281/zenodo.22283967Record set: EC-MECH campaign (EC-MECH-001 pilot + EC-MECH-002)Related to: EC-STORAGE-001, DOI 10.5281/zenodo.21299091 Research question: Can the coherence lifetime of an entangled multi-qubit state be predicted from the measured coherence losses of its individual qubits? Plain language summa...
Posterior Ontology Memory (POM) models uncertainty in the vocabulary used by a symbolic memory, rather than assuming that its semantic schema is fixed. It treats mappings from surface predicates to latent semantic categories as uncertain and carries that uncertainty into prediction. The model combines a partition prior...
Thermal infrared remote sensing has reached a turning point. A status audit completed for this review identifies 55 operational satellite platform deployments on 18 August 2026. The resulting dataset contains 174 named thermal infrared instrument designs mapped to 306 historical, operational and planned satellite platf...
A task-oriented dialogue agent that simulates emergency call takers to prepare citizens for effective medical emergency communication and uses a finite-state machine as its dialogue policy and large language models for natural language understanding.
An adaptive evolutionary framework for TS search workflows that prioritizes completion of a target dataset over global algorithmic robustness and suggests that adaptive, LLM-driven evolutionary workflow optimization provides a transferable strategy for improving validated TS coverage in large-scale, failure-prone scien...
An automated, data quality-oriented preprocessing pipeline that rewrites radiology reports at the sentence level to reduce external references is developed and can serve as an effective preprocessing step for improving the suitability of chest X-ray report datasets for multimodal model development.
Vision-language models (VLMs) are increasingly used to measure urban change from repeated street-level imagery, and the results are often mapped for individual sample points. Such maps assume that a perception score changes only if the street does. We test this assumption with repeated Google Street View captures of un...
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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.
We’re giving developers, enterprises, scientists, and consumers access to Gemini 4 Argon, our latest frontier model.
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