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Related Experiment Video

Updated: Sep 14, 2025

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

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Published on: October 4, 2015

NIT: A dataset for network intent translation.

Ala' A AlSamarneh¹, Omar Y Al-Jarrah¹, Ahmad T Al-Hammouri^1,2

¹Department of Network Engineering and Security, Jordan University of Science and Technology, Irbid, 22110, Jordan.

|July 21, 2025

Summary

This summary is machine-generated.

The Network Intent Translations (NIT) dataset offers natural language to network configuration translations for Juniper devices. This resource aids research in automating network management through intent-based networking.

Keywords:

Intent-based networks Intent-translation LLM Network-configurations

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Area of Science:

Computer Science
Network Engineering

Background:

Network configuration is complex and often manual.
Automating network management requires translating high-level intents into low-level configurations.

Purpose of the Study:

Introduce the Network Intent Translations (NIT) dataset.
Facilitate research in network intent translation, specifically intent-to-vendor translations.

Main Methods:

The NIT dataset comprises 1000 entries, each a JSON object with question (intent), context, and answer (configuration).
Data was generated and validated for Juniper EX3300 switches running JUNOS, ensuring syntactic correctness.

Main Results:

The dataset provides natural language intents mapped to Juniper device configurations.
It focuses on translation accuracy, not parameter value validation or conflict resolution.

Conclusions:

The NIT dataset is a valuable resource for advancing network intent translation research.
It supports the development of automated network management solutions.