activity
20192025
most citedMapping the Landscape of Artificial Intelligence Applications against COVID-19

347 citations · 1k across the 30 of their papers we have counts for

collaborators
Showing 2021Show all

6 papers · 1 filter

cs.CY2021

A Framework for Deprecating Datasets: Standardizing Documentation, Identification, and Communication

Alexandra Sasha Luccioni, Frances Corry, Hamsini Sridharan +3

Datasets are central to training machine learning (ML) models. The ML community has recently made significant improvements to data stewardship and documentation practices across th…

cs.CV2021★ 2 cited

ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods

Victor Schmidt, Alexandra Sasha Luccioni, Mélisande Teng +8

Climate change is a major threat to humanity, and the actions required to prevent its catastrophic consequences include changes in both policy-making and individual behaviour. Howe…

cs.CL2021★ 1 cited

Ensuring the Inclusive Use of Natural Language Processing in the Global Response to COVID-19

Alexandra Sasha Luccioni, Katherine Hoffmann Pham, Cynthia Sin Nga Lam +2

Natural language processing (NLP) plays a significant role in tools for the COVID-19 pandemic response, from detecting misinformation on social media to helping to provide accurate…

cs.CY2021★ 8 cited

Automated Identification of Climate Risk Disclosures in Annual Corporate Reports

David Friederich, Lynn H. Kaack, Alexandra Luccioni +1

It is important for policymakers to understand which financial policies are effective in increasing climate risk disclosure in corporate reporting. We use machine learning to autom…

cs.CL2021★ 18 cited

What's in the Box? A Preliminary Analysis of Undesirable Content in the Common Crawl Corpus

Alexandra Sasha Luccioni, Joseph D. Viviano

Whereas much of the success of the current generation of neural language models has been driven by increasingly large training corpora, relatively little research has been dedicate…

cs.CV2021

Geo-Spatiotemporal Features and Shape-Based Prior Knowledge for Fine-grained Imbalanced Data Classification

Charles A. Kantor, Marta Skreta, Brice Rauby +5

Fine-grained classification aims at distinguishing between items with similar global perception and patterns, but that differ by minute details. Our primary challenges come from bo…