Green AI

604 indexed citations

Abstract

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About

This paper, published in 2020, received 604 indexed citations. Written by Roy Schwartz, Jesse Dodge, Noah A. Smith and Oren Etzioni covering the research area of Environmental Engineering. It is primarily cited by scholars working on Artificial Intelligence (250 citations), Computer Vision and Pattern Recognition (124 citations) and Electrical and Electronic Engineering (123 citations). Published in Communications of the ACM.

In The Last Decade

doi.org/10.1145/3381831 →

Countries where authors are citing Green AI

Specialization
Citations

This map shows the geographic impact of Green AI. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Green AI with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Green AI more than expected).

Fields of papers citing Green AI

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Green AI. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Green AI.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.1145/3381831.

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