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Intent2Tc: Automated Intent-to-Traffic Control Translation with Language Models

Paper recorded by Signals 4 on 2026-09-25 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-25 on arXiv · recorded by Signals 4 on 2026-09-28

Category: cs.CL · 自然语言处理 · first seen 2026-09-28

Abstract

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 Int

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#9 most recent of 267 cs.CL papers we have recorded · ↑ newer: Sorry Robot, Happy Human: Vision-Language Models Read Only One of Two · ↓ older: Highlight-Then-Summarize: Learning to Compress Evidence for Long-Conte
Cite this page: Intent2Tc: Automated Intent-to-Traffic Control Translation with Language Models: the #9 most recent of 267 cs.CL papers we have recorded (as of 2026-09-25). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/intent2tc-automated-intent-to-traffic-control-translation-with-language-models.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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