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Paper Citation Record · LEDGER

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint

As of 14 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2608.09998.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2608.09998 v1

Coverage vector

measured 64 of 64 reference resolution

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measured 64 of 64 standing notices

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measured 0 of 0 inbound itemization

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Reference resolution

64 of 64 outbound references displayed

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External citation measurements

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Outbound references

Observation 6d59af30-7741-4f68-8f02-f8bf4d856762 · outbound

This paper cites Wiley Inter- disciplinary Reviews: Data Mining and Knowledge Discovery13(4), 1507 (2023) https://doi.org/10.1002/widm.1507.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Wiley Inter- disciplinary Reviews: Data Mining and Knowledge Discovery13(4), 1507 (2023) https://doi.org/10.1002/widm.1507

Reference 1

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This paper cites Tackling Climate Change with Machine Learning.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Tackling Climate Change with Machine Learning

Reference 2

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This paper cites Energy and Policy Considerations for Deep Learning in NLP.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Energy and Policy Considerations for Deep Learning in NLP

Reference 3

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This paper cites Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning

Reference 4

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This paper cites arXiv preprint (2022) https://doi.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint arXiv preprint (2022) https://doi

Reference 5

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This paper cites Nature Publishing Group UK London.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Nature Publishing Group UK London

Reference 6

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This paper cites Communications of the ACM63(12), 54–63 (2020) https://doi.org/10.1145/3381831.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Communications of the ACM63(12), 54–63 (2020) https://doi.org/10.1145/3381831

Reference 7

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This paper cites A Survey on Green Deep Learning.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint A Survey on Green Deep Learning

Reference 8

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This paper cites bmj372 (2021) https://doi.org/10.1136/bmj.n71.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint bmj372 (2021) https://doi.org/10.1136/bmj.n71

Reference 9

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This paper cites In: Proceedings of the 18th International Con- ference on Evaluation and Assessment in Software Engineering, pp.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint In: Proceedings of the 18th International Con- ference on Evaluation and Assessment in Software Engineering, pp

Reference 10

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This paper cites AI and Ethics1(3), 213–218 (2021) https://doi.org/10.1007/ s43681-021-00043-6 24.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint AI and Ethics1(3), 213–218 (2021) https://doi.org/10.1007/ s43681-021-00043-6 24

Reference 11

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This paper cites AMCIS 2022 Proceedings (2022).

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint AMCIS 2022 Proceedings (2022)

Reference 12

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This paper cites IEEE Access12, 23989–24013 (2024) https://doi.org/10.1109/ ACCESS.2024.3360705.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint IEEE Access12, 23989–24013 (2024) https://doi.org/10.1109/ ACCESS.2024.3360705

Reference 13

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This paper cites https://datacenters.google/ operating-sustainably.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint https://datacenters.google/ operating-sustainably

Reference 14

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This paper cites Reuters (2024).

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Reuters (2024)

Reference 15

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint DataCenterDynamics (2024)

Reference 16

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This paper cites In: ECAI 2024, pp.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint In: ECAI 2024, pp

Reference 17

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This paper cites Emerging Science Journal8(4), 1602–1621 (2024) https://doi.org/10.28991/ESJ-2024-08-04-021.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Emerging Science Journal8(4), 1602–1621 (2024) https://doi.org/10.28991/ESJ-2024-08-04-021

Reference 18

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint HighTech and Innovation Journal 5(4), 1085–1100 (2024) https://doi.org/10.28991/HIJ-2024-05-04-015

Reference 19

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Emerging Science Journal8(3), 933–947 (2024) https://doi.org/10.28991/ ESJ-2024-08-03-08

Reference 20

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This paper cites Sustainable AI: Environmental Implications, Challenges and Opportunities.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Sustainable AI: Environmental Implications, Challenges and Opportunities

Reference 21

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This paper cites Quantifying the Carbon Emissions of Machine Learning.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Quantifying the Carbon Emissions of Machine Learning

Reference 22

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This paper cites On the Opportunities of Green Computing: A Survey.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint On the Opportunities of Green Computing: A Survey

Reference 23

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This paper cites Green Algorithms: Quantifying the carbon footprint of computation.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Green Algorithms: Quantifying the carbon footprint of computation

Reference 24

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This paper cites Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective

Reference 25

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Mach Learn Tech Rep1(1), 1–6 (2014) https://doi.org/10.13140/RG.2.2.28948.04489

Reference 26

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Tall´ on-Ballesteros, A.: The impact of data normalization on the accuracy of machine learning algorithms: A comparative analysis

Reference 27

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This paper cites Neuroinformatics12(2), 229–244 (2014) https://doi.org/10.1007/ s12021-013-9204-3.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Neuroinformatics12(2), 229–244 (2014) https://doi.org/10.1007/ s12021-013-9204-3

Reference 28

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Journal of Machine Learning Research10(66-71) (2009)

Reference 29

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This paper cites Further advantages of data augmentation on convolutional neural networks.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Further advantages of data augmentation on convolutional neural networks

Reference 30

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This paper cites IEEE Transactions on Knowledge and Data Engineering (2025) https://doi.org/10.1109/TKDE.2025.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint IEEE Transactions on Knowledge and Data Engineering (2025) https://doi.org/10.1109/TKDE.2025

Reference 31

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Fixup Initialization: Residual Learning Without Normalization

Reference 32

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint All you need is a good init

Reference 33

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Layer Normalization

Reference 35

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Group Normalization

Reference 36

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This paper cites Greedy Layerwise Learning Can Scale to ImageNet.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Greedy Layerwise Learning Can Scale to ImageNet

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This paper cites https://openreview.net/forum? id=ryZ8sz-Ab.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint https://openreview.net/forum? id=ryZ8sz-Ab

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This paper cites Advances in neural information processing systems2(1989).

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Advances in neural information processing systems2(1989)

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This paper cites ACM Computing Surveys55(12), 1–37 (2023).

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint ACM Computing Surveys55(12), 1–37 (2023)

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This paper cites Language model compression with weighted low-rank factorization.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Language model compression with weighted low-rank factorization

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This paper cites arXiv preprint (2018) https://doi.org/10.48550/arXiv.1806.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint arXiv preprint (2018) https://doi.org/10.48550/arXiv.1806

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Distilling the Knowledge in a Neural Network

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Reference 44

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This paper cites nature521(7553), 436–444 (2015) https://doi.org/10.1038/nature14539.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint nature521(7553), 436–444 (2015) https://doi.org/10.1038/nature14539

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Unresolved cited work

Reference 46

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This paper cites In: 2022 International Conference on ICT for Sustainability (ICT4S), pp.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint In: 2022 International Conference on ICT for Sustainability (ICT4S), pp

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint In: 2023 IEEE 20th International Conference on Software Architecture Companion (ICSA-C), pp

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint In: Proceedings of the Second Workshop on Simple and Efficient Natural Language Processing, pp

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint In: Doklady Mathematics, vol

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Energy Usage Reports: Environmental awareness as part of algorithmic accountability

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Accessed: 2024-06-26 (2023)

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Semester Project, EPFL (2020)

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint In: 2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA), pp

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This paper cites IEEE Access11, 51199–51213 (2023) https://doi.org/10.1109/ACCESS.2023.3280191.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint IEEE Access11, 51199–51213 (2023) https://doi.org/10.1109/ACCESS.2023.3280191

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint In: International Conference on Medical Image Computing and Computer-assisted Intervention, pp

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recog- nition, pp

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Advancing Green AI: Efficient and Accurate Lightweight CNNs for Rice Leaf Disease Identification

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint In: 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC), pp

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint In: 2021 Interna- tional Conference on Disruptive Technologies for Multi-disciplinary Research and Applications (CENTCON), vol

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This paper cites IEEE transactions on pattern analysis and machine intelligence30(11), 1958–1970 (2008) https://doi.org/10.

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint IEEE transactions on pattern analysis and machine intelligence30(11), 1958–1970 (2008) https://doi.org/10

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This paper cites University of Toronto18268744(2009).

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint University of Toronto18268744(2009)

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint Carbon Emissions and Large Neural Network Training

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Pith citing papers

No inbound Pith citation observations are available.