White paper
Holistic framework for AI in critical network infrastructures
This document establishes the main foundations of the AI4REALNET project, in particular, the following key outcomes: - The formal specification of domain-specific use cases (UCs), replicating real-world operating scenarios involving human operator
White paper
Position paper on AI for the operation of critical energy and mobility network infrastructures
This position paper outlines AI4REALNET’s approach to applying AI in network infrastructure operations, translating application needs into algorithmic proposals for effective human-AI collaboration in decision-making processes.
Article/Books/eBooks
An Open Dataset of Synthetic Speech
This paper introduces a multilingual, multispeaker dataset composed of synthetic and natural speech, designed to foster research and benchmarking in synthetic speech detection.
Software resources
Word-Class Embeddings for Multiclass Text Classification
Code for Word-Class Embeddings (WCEs), a form of supervised embeddings especially suited for multiclass text classification.
Software resources
Neighborhood Contrastive Learning for Novel Class Discovery
A holistic learning framework for Novel Class Discovery (NCD), which adopts contrastive learning to learn discriminate features with both the labeled and unlabeled data.
Software resources
Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation
we study the task of synthetic-to-real domain generalized semantic segmentation, which aims to learn a model that is robust to unseen real-world scenes using only synthetic data.