Sustainability of TSFM Deployment and Pretraining: From Carbon Footprint Analysis to Mitigation via Pruning
Paper recorded by Signals 4 on 2026-10-23 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-23 on arXiv · recorded by Signals 4 on 2026-10-26
Category: cs.LG · 机器学习 · first seen 2026-10-26
Abstract
Time Series Foundation Models (TSFMs) offer strong zero-shot forecasting capabilities, but their high pretraining cost raises a practical sustainability question: does this upfront investment pay off over a full deployment lifecycle, compared to supervised standalone models that must be periodically retrained? We model the cumulative carbon cost of different approaches across a realistic industria
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Cite this page: Sustainability of TSFM Deployment and Pretraining: From Carbon Footprint Analysis to Mitigation via Pruning: the #190 most recent of 749 cs.LG papers we have recorded (as of 2026-10-23). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/sustainability-of-tsfm-deployment-and-pretraining-from-carbon-footprint-analysis.html
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