cs.NI · 2026-09-28 · No. 127
Networking and Internet Architecture, 2026-09-28.
4 new papers in cs.NI. Titles, authors,
abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →
01 — The papers
4 entries-
01
Can You Check That? The Checkability Boundary for Local LLM Network Automation
Maleeha Masood, Momina Nofal
cs.NI · cs.AI
Sending every network-automation input to a third-party frontier LLM exports sensitive artifacts such as production configurations, topologies, and logs. Querying small language models (SLMs) locally avoids this egress, but SLM outputs can be error-prone for direct use. This work introduces checkability as a criterion for determining which tasks are suitable for local inference. A task is checkable when it exposes a cheap, deterministic test...
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02
ITS Fairy: Occlusion Assistance Selected Against a Recipient's Own Perception Reports
Yenan Wang, Oscar Karlsson, Elad Michael Schiller, Francesco Raviglione, Claudio Casetti
cs.NI · cs.DC
Cooperative perception can expose object state beyond a vehicle's onboard sensors, but sensing occlusion can still leave a local safety application without the objects its collision computation needs. To tackle this challenge, we present the ITS Fairy, an infrastructure-side Server Local Dynamic Map (S-LDM) service whose decision unit is the pair (recipient, missing conflict-relevant object): among objects absent from a recipient's...
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03
Intent2Tc: Automated Intent-to-Traffic Control Translation with Language Models
Andrea Masini, Sudipta Acharya, Paolo Bellavista, Luca Foschini, Burak Kantarci
cs.NI · cs.AI · cs.CL
Automated and highly usable Quality-of-Service (QoS) enforcement requires translating high-level service intents into deployable traffic-management policies. Although intent-based networking (IBN) has simplified policy specification, bridging the gap between business-level intents and executable network configurations remains complex, error-prone, and difficult to automate. This paper presents Intent2Tc, a closed-loop language-model-driven...
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04
Unknown-Traffic Detection, Calibration and Shortcut Reliance in Distilled Encrypted-Traffic Classifiers over One Year
Mahmoud Abbasi
cs.NI · cs.LG
Knowledge distillation is the standard way to compress encrypted-traffic classifiers for the edge, and almost all such work judges students by accuracy alone. We ask what else a student inherits: unknown-traffic detection, calibration, shortcut reliance, and whether any survives a year of drift. Resemblance proves little on its own, since soft targets also regularise. We therefore distil one 101k-parameter student from two teachers of equal...
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