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Natural-XAI: Explainable AI with Natural Language Explanations
Oana-Maria Camburu · Zeynep Akata

Mon Jul 19 08:00 AM -- 11:00 AM (PDT) @ Virtual

In this tutorial, we will present the emerging direction of explainability that we will refer to as Natural-XAI. Natural-XAI aims to build AI models that (1) learn from natural language explanations for the ground-truth labels at training time, and (2) provide such explanations for their predictions at deployment time. For example, a self-driving car would not only see at training time that it has to stop in a certain environment, but it would additionally be told why this is the case, e.g., “Because the traffic light in front is red.”. At usage time, the self-driving car would also be able to provide such natural language explanations for its actions, thus reassuring the passengers. This direction has recently received increasingly large attention.

Mon 8:00 a.m. - 8:05 a.m.
Live Introduction (Live intro)
Mon 8:05 a.m. - 9:10 a.m.
Part One (Talk)   
Oana-Maria Camburu
Mon 9:10 a.m. - 9:25 a.m.
Q&A Part One (Q&A)
Oana-Maria Camburu, Zeynep Akata
Mon 9:25 a.m. - 9:40 a.m.
Mon 9:40 a.m. - 10:45 a.m.
Part Two (Talk)   
Zeynep Akata
Mon 10:45 a.m. - 11:00 a.m.
Q&A Part Two (Q&A)
Oana-Maria Camburu, Zeynep Akata

Author Information

Oana-Maria Camburu (University of Oxford)
Zeynep Akata (University of Tübingen)

Zeynep Akata is a professor of Computer Science (W3) within the Cluster of Excellence Machine Learning at the University of Tübingen. After completing her PhD at the INRIA Rhone Alpes with Prof Cordelia Schmid (2014), she worked as a post-doctoral researcher at the Max Planck Institute for Informatics with Prof Bernt Schiele (2014-17) and at University of California Berkeley with Prof Trevor Darrell (2016-17). Before moving to Tübingen in October 2019, she was an assistant professor at the University of Amsterdam with Prof Max Welling (2017-19). She received a Lise-Meitner Award for Excellent Women in Computer Science from Max Planck Society in 2014, a young scientist honour from the Werner-von-Siemens-Ring foundation in 2019 and an ERC-2019 Starting Grant from the European Commission. Her research interests include multimodal learning and explainable AI.

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