---
title: "Electrical and Electronic Engineering — papers"
description: "Electrical and Electronic Engineering: 7 papers of the Elamur Research library, the most cited first — our summary of each, its ideas, references and who…"
canonical: "https://research.elamur.ai/free/en/shelves/engineering/electrical-and-electronic-engineering/"
---
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# ⚙️ Electrical and Electronic Engineering

7 papers · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Electrical and Electronic Engineering is a subfield of Engineering in the OpenAlex classification of science. The topics most of its papers here are on: «Green IT and Sustainability», «Low-power high-performance VLSI design».

## Papers

1. [**Energy and Policy Considerations for Deep Learning in NLP**Emma Strubell, Ananya Ganesh, Andrew McCallum*2019 · 4,049 citations*](https://md.research.elamur.ai/free/en/papers/strubell-2019-energy-policy-considerations-deep-learning/)
2. [**Green AI**Roy Schwartz, Jesse Dodge, Noah A. Smith, et al.*2019 · 370 citations*](https://md.research.elamur.ai/free/en/papers/schwartz-2019-green-ai/)
3. [**Quantifying the Carbon Emissions of Machine Learning**Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, et al.*2019 · 324 citations*](https://md.research.elamur.ai/free/en/papers/lacoste-2019-quantifying-carbon-emissions-machine-learning/)
4. [**Carbon Emissions and Large Neural Network Training**David Patterson, Joseph Gonzalez, Quoc Le, et al.*2021 · 304 citations*](https://md.research.elamur.ai/free/en/papers/patterson-2021-carbon-emissions-large-neural-network/)
5. [**From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inference**Siddharth Samsi, Dan Zhao, Joseph McDonald, et al.*2023 · 288 citations*](https://md.research.elamur.ai/free/en/papers/samsi-2023-words-watts-benchmarking-energy-costs/)
6. [**QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs**Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, et al.*2024 · 252 citations*](https://md.research.elamur.ai/free/en/papers/ashkboos-2024-quarot-outlier-free-4-bit/)
7. [**SqueezeLLM: Dense-and-Sparse Quantization**Sehoon Kim, Coleman Hooper, Amir Gholami, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-squeezellm-dense-sparse-quantization/)

Updated 23 October 2026

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