AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 5 of 9 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
This work organizes 82 reusable methods from Putnam 2000-2014 as Method Contracts, which pair applicability descriptions with Mathlib anchors, a checked example or scaffold, and expected proof obligations, and analyzes when similarity-based representations cannot distinguish methods with different applicability, how er...
Large language models (LLMs) have reached expert-level performance on competition mathematics largely through the volume of search placed around them: candidate solutions are sampled in quantity and retained only when an external criterion accepts them. Such a procedure improves the outcome that survives it while leavi...
Agent harnesses govern how large language models (LLMs) gather context, invoke tools, verify results, preserve state, and terminate, largely affecting agent performance. However, the value of each harness mechanism can differ across heterogeneous tasks: a mechanism that improves one task may impose overhead or context...
ANTMAN is introduced, an adaptive coordination framework that treats evolving unresolved information needs as the unit of runtime coordination and maintains a revisable Need Graph that tracks unresolved requirements, accumulated evidence, prior attempts, and search progress.
A synthetic player population is constructed whose traits are ground truth by construction, and an opportunity-aware decision-moment representation is introduced that disentangles preference from the chance to express it; ablating it selectively degrades opportunity-dependent traits.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.