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Sustainable AI: Environmental Implications, Challenges and Opportunities
Conference on Machine Learning and Systems (MLSys), 2021
30 October 2021
Carole-Jean Wu
Ramya Raghavendra
Udit Gupta
Bilge Acun
Newsha Ardalani
Kiwan Maeng
Gloria Chang
Fiona Aga Behram
James Huang
Charles Bai
M. Gschwind
Anurag Gupta
Myle Ott
Anastasia Melnikov
Salvatore Candido
David Brooks
Geeta Chauhan
Benjamin C. Lee
Hsien-Hsin S. Lee
Bugra Akyildiz
Maximilian Balandat
Joe Spisak
R. Jain
Michael G. Rabbat
K. Hazelwood
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Papers citing
"Sustainable AI: Environmental Implications, Challenges and Opportunities"
50 / 192 papers shown
Title
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Task-Aware Reduction for Scalable LLM-Database Systems
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Boomerang Distillation Enables Zero-Shot Model Size Interpolation
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Choosing to Be Green: Advancing Green AI via Dynamic Model Selection
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24 Sep 2025
Video Killed the Energy Budget: Characterizing the Latency and Power Regimes of Open Text-to-Video Models
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Regis Pierrard
Sasha Luccioni
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Green Recommender Systems: Understanding and Minimizing the Carbon Footprint of AI-Powered Personalization
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Alan Said
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Data-Efficient Ensemble Weather Forecasting with Diffusion Models
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Ziyang Liu
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Virtual Agent Economies
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Simon Osindero
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Rahul Mazumder
162
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Gu-Yeon Wei
David Brooks
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MRM3: Machine Readable ML Model Metadata
ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services (MobiSys), 2025
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Blaž Bertalanič
Marko Grobelnik
Carolina Fortuna
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How Do Companies Manage the Environmental Sustainability of AI? An Interview Study About Green AI Efforts and Regulations
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One Search Fits All: Pareto-Optimal Eco-Friendly Model Selection
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CarbonCall: Sustainability-Aware Function Calling for Large Language Models on Edge Devices
Varatheepan Paramanayakam
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282
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Ruicheng Ao
Gan Luo
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Green MLOps to Green GenOps: An Empirical Study of Energy Consumption in Discriminative and Generative AI Operations
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Ioannis Mavromatis
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Maximilian Schmidt
George Dasoulas
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Stefano Attademo
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Tim Hoffmann
Michael Keckeisen
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Green Prompting
Marta Adamska
Daria Smirnova
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Christopher Kanan
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Ecomap: Sustainability-Driven Optimization of Multi-Tenant DNN Execution on Edge Servers
IEEE transactions on computers (IEEE Trans. Comput.), 2025
Varatheepan Paramanayakam
Andreas Karatzas
Dimitrios Stamoulis
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206
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Dong In Kim
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Holistically Evaluating the Environmental Impact of Creating Language Models
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Life-Cycle Emissions of AI Hardware: A Cradle-To-Grave Approach and Generational Trends
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GreenAuto: An Automated Platform for Sustainable AI Model Design on Edge Devices
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Onur Altintas
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Constrained Hybrid Metaheuristic Algorithm for Probabilistic Neural Networks Learning
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On the Ethical Considerations of Generative Agents
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