Alessandra Russo

Saliency Maps Generation for Automatic Text Summarization

2019 · arXiv (Cornell University)

Saliency map generation techniques are at the forefront of explainable AI literature for a broad range of machine learning applications. Our goal is to question the limits of these approaches on more complex tasks. In …

Learning Diverse Representations for Fast Adaptation to Distribution Shift

2020 · arXiv (Cornell University)

The i.i.d. assumption is a useful idealization that underpins many successful approaches to supervised machine learning. However, its violation can lead to models that learn to exploit spurious correlations in the training data, rendering them …

On the Transferability of VAE Embeddings using Relational Knowledge with Semi-Supervision

2020 · arXiv (Cornell University)

We propose a new model for relational VAE semi-supervision capable of balancing disentanglement and low complexity modelling of relations with different symbolic properties. We compare the relative benefits of relation-decoder complexity and latent space structure …