34 citations · 113 across the 36 of their papers we have counts for
5 papers · 1 filter
Estimating the Adversarial Robustness of Attributions in Text with Transformers
Adam Ivankay, Mattia Rigotti, Ivan Girardi +2
Explanations are crucial parts of deep neural network (DNN) classifiers. In high stakes applications, faithful and robust explanations are important to understand and gain trust in…
Active Learning for Imbalanced Civil Infrastructure Data
Thomas Frick, Diego Antognini, Mattia Rigotti +3
Aging civil infrastructures are closely monitored by engineers for damage and critical defects. As the manual inspection of such large structures is costly and time-consuming, we a…
Model-Assisted Labeling via Explainability for Visual Inspection of Civil Infrastructures
Klara Janouskova, Mattia Rigotti, Ioana Giurgiu +1
Labeling images for visual segmentation is a time-consuming task which can be costly, particularly in application domains where labels have to be provided by specialized expert ann…
Compositional generalization through abstract representations in human and artificial neural networks
Takuya Ito, Tim Klinger, Douglas H. Schultz +3
Humans have a remarkable ability to rapidly generalize to new tasks that is difficult to reproduce in artificial learning systems. Compositionality has been proposed as a key mecha…
Cloud-Based Real-Time Molecular Screening Platform with MolFormer
Brian Belgodere, Vijil Chenthamarakshan, Payel Das +9
With the prospect of automating a number of chemical tasks with high fidelity, chemical language processing models are emerging at a rapid speed. Here, we present a cloud-based rea…