302 citations · 1.5k across the 104 of their papers we have counts for
108 papers
Exploiting T-norms for Deep Learning in Autonomous Driving
Mihaela Cătălina Stoian, Eleonora Giunchiglia, Thomas Lukasiewicz
Deep learning has been at the core of the autonomous driving field development, due to the neural networks' success in finding patterns in raw data and turning them into accurate p…
NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentation
Jianfeng Wang, Daniela Massiceti, Xiaolin Hu +2
Semi-supervised semantic segmentation involves assigning pixel-wise labels to unlabeled images at training time. This is useful in a wide range of real-world applications where col…
Brain-inspired Computational Intelligence via Predictive Coding
Tommaso Salvatori, Ankur Mali, Christopher L. Buckley +4
Artificial intelligence (AI) is rapidly becoming one of the key technologies of this century. The majority of results in AI thus far have been achieved using deep neural networks t…
Faithfulness Tests for Natural Language Explanations
Pepa Atanasova, Oana-Maria Camburu, Christina Lioma +3
Explanations of neural models aim to reveal a model's decision-making process for its predictions. However, recent work shows that current methods giving explanations such as salie…
An Empirical Analysis of Parameter-Efficient Methods for Debiasing Pre-Trained Language Models
Zhongbin Xie, Thomas Lukasiewicz
The increasingly large size of modern pretrained language models not only makes them inherit more human-like biases from the training corpora, but also makes it computationally exp…
KNOW How to Make Up Your Mind! Adversarially Detecting and Alleviating Inconsistencies in Natural Language Explanations
Myeongjun Jang, Bodhisattwa Prasad Majumder, Julian McAuley +2
While recent works have been considerably improving the quality of the natural language explanations (NLEs) generated by a model to justify its predictions, there is very limited r…