mlsanityData to 7 Oct 2026

Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Models

arXiv 2306.16668 ↗First posted 29 Jun 2023cs.IRcited by 6

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Abstract (arXiv)

As in other fields of artificial intelligence, the information retrieval community has grown interested in investigating the power consumption associated with neural models, particularly models of search. This interest has become particularly relevant as the energy consumption of information retrieval models has risen with new neural models based on large language models, leading to an associated increase of CO2 emissions, albeit relatively low compared to fields such as natural language processing.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Jun 2023.

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Citing papers per year: 2024: 4; 2025: 1; 2026: 1.

6 papers.