First poster session

Explaining Siamese Networks in Few-Shot Learning 1 1

Andrea Fedele

Generative Models for Decision Trees 1 1

Mattia Setzu

Understanding and Exploiting the Latent Space to Improve Machine Learning models eXplainability 1 2

Fosca Giannotti,Riccardo Guidotti,Simone Piaggesi

Trust and Reliance in AI: Design for appropriate Human-AI collaboration 1 3

Andrea Beretta

A Frank System for Hybrid Decision Making 1 3

Federico Mazzoni

PyFlowML: Enhancing ML-based Decision Making through Visual Language 1 4

Tommaso Turchi

DNN Benchmarks for Selective Classification 2 2

Andrea Pugnana

Correlation and Unintended Biases on Univariate and Multivariate Decision Trees 2 2

Mattia Setzu

Critical points and convergence analysis of generative deep neural networks trained with Bures-Wasserstein loss 2 4

Katerina Papagiannouli

Global optimality of Elman-type recurrent neural networks in the mean-field regime 2 4

Andrea Agazzi

Gaussian processes based data augmentation and expected signature for time series classification 2 4

Marco Romito

Continual Learning & Compositionality for Sustainable AI 3 2

Luigi Quarantiello

Towards the Development of Text-Image Patent Datasets for Enhancing Engineering Design 3 3

Vito Giordano, Marco Consoloni

Explainability for Deep Graph Networks 3 3

Michele Fontanesi

ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models 3 5

Andrea Pedrotti

Kernel density estimation for multiclass quantification 3 5

Alejandro Moreo

Using Quantification to Predict Classifier Accuracy under Prior Probability Shift 3 5

Fabrizio Sebastiani

Assessing Language-and-Vision Language Models on Event Plausibility 3 6

Maria Cassese

Fake news may be coming in your language: A case study on Italian 3 6

Giovanni Puccetti

Social bias anaysis in text-to-image Large Language Models 3 6

Alessandro Bondielli, Lucia Passaro

What do Large Language Models know about causality? 3 6

Martina Miliani, Alessandro Lenci