AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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8,685 papers
LibraryDesignBench is introduced, a two-phase benchmark in which an agent implements a full-featured library from a specification that defines required capabilities and potential use cases without prescribing the design.
Pretrained transformers use little of their depth to follow references in context. Thirteen base models reliably follow only 1.4-3.6 lines, and extra pretrained loops add little. A task-trained rank-8 LoRA at one early layer extends this computation with all model weights frozen. Qwen3-8B improves from 15.5% to 99% exa...
The Optimal Transport-based Robust Off-Policy Evaluation (OTROPE) is proposed, a likelihood-free evaluation that performs distributional correction in a semantic space via optimal transport to align labeled behavior-policy samples with unlabeled target-policy samples, yielding a doubly robust-style evaluation.
REST (REpresentation-Supervised Thoughts), a training objective that turns four properties of a valid thought representation into differentiable losses added to CE, instantiate in latent single-agent and multi-agent systems, without architectural changes or added parameters at inference.
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GeoOutageBench provides a design principle and foundation for assessing LLM-KG systems that support real-world infrastructure resilience analysis and provides user-configurable evaluation of three important, highly coherent yet less studied tasks.
This work develops a conception of understanding fit for polyphonic AI that centres on sound circuitry that is reliably and correctly recruited and in control of outputs, and can do the work of guiding trust in AI.
This work quantifies the compression cost of boundaries while separating it from the prediction quality of the resulting token units, and introduces boundary licences, which limit the vocabulary entries permitted to cross cuts and admit the same form of certificate.
This work presents a neurosymbolic router that classifies each incoming query and dispatches it to the cheapest correct solver, sending structured tasks to deterministic engines and reserving the small language model (SLM) for open-ended word problems.
A Wizard-of-Oz study design and supporting real-time system for collecting multimodal behavioral data from native Chinese speakers reacting to social norm violations by German learners.
This paper presents AuditBench, a new benchmark dataset for evaluating the capabilities of LLMs at investigating security-related system audit logs. We design and use this benchmark to explore the performance of LLMs on four log-investigation tasks that incident response teams commonly perform, ranging from triaging al...
This work formalizes agent attribution as a cooperative game, parameterized by the coalition distribution, intervention protocol, and target metric, which provides a principled approach for cost-effective MAS attribution and intervention.
The rapid growth of online video platforms and AI-generated content has made reliable video guardrails a key challenge for safety and real-world deployment. While most videos can be screened through fast pattern recognition, a small subset requires deeper reasoning over temporally complex content and nuanced policy con...
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
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.
A new language-processing tool could help identify the highest-risk individuals from natural language, enabling swifter interventions.
A Blog post by Liquid AI on Hugging Face
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