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2023

Trends in Explainable AI (XAI) Literature

Jacovi, Alon

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The XAI literature is decentralized, both in terminology and in publication venues, but recent years saw the community converge around keywords that make it possible to more reliably discover papers automatically.

We use keyword search using the SemanticScholar API and manual curation to collect a well-formatted and reasonably comprehensive set of 5199 XAI papers, available at https://github.com/alonjacovi/XAI-Scholar .
We use this collection to clarify and visualize trends about the size and scope of the literature, citation trends, cross-field trends, and collaboration trends.
Overall, XAI is becoming increasingly multidisciplinary, with relative growth in papers belonging to increasingly diverse (non-CS) scientific fields, increasing cross-field collaborative authorship, increasing cross-field citation activity.

Trends in Explainable AI (XAI) Literature · Around

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A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems
Original
Sina Mohseni, Niloofar Zarei, and Eric D Ragan. 2018 · 2018
Earlier work this paper cites.
All-about-XAI
Anyifei. 2019 · 2019
Earlier work this paper cites.
The evolution of citation graphs in artificial intelligence research
Morgan Frank, Dashun Wang, Manuel Cebrian, and Iyad Rahwan. 2019 · 2019
Earlier work this paper cites.
A Survey of the State of Explainable AI for Natural Language Processing
Marina Danilevsky, Kun Qian, Ranit Aharonov, Yannis Katsis, Ban Kawas, and Prithviraj Sen. 2020 · 2020
Earlier work this paper cites.
Awesome Interpretable Machine Learning
Michal Lopuszynski. 2020 · 2020
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Then

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