Nathan Cooper
Nathan Cooper has 3 papers in our library, in 2024, most of them on Efficient models & compression; often with Ashish Datta, Dakota Mahan, Duy Phung.
OpenAlex · ORCID · Wikidata · h-index 12 · 25 works · 812 citations OpenAlex, 2026-10-14
📄 3 works in our library · 🔗 Cited 376 times in our library · ⭐ Paper Stars ranking: #4271
Affiliations
Fields, topics and concepts
📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksInformation Systems · 2 worksComputer Science Applications · 1 work
🧭 Topics 1Research subjects and languages the work is about.Efficient models & compression · 1 work
Works by year
2020s
Papers
- Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference (2024 · 358 citations)
BERT-style encoders still power many retrieval, classification and RAG pipelines, yet most deployments rely on old models. - Stable LM 2 1.6B Technical Report (2024 · 46 citations)
Many strong language models are released without their training data or full recipe, which makes independent replication nearly impossible. - Stable Code Technical Report (2024 · 9 citations)
Code assistants such as autocomplete tools are called constantly, so a model compact enough to run locally on consumer hardware avoids network delays and dependence on gated APIs.
Co-authors here
- Ashish Datta ×2
- Dakota Mahan ×2
- Duy Phung ×2
- James Baicoianu ×2
- Jonathan Tow ×2
- Maksym Zhuravinskyi ×2
- Marco Bellagente ×2
- Reshinth Adithyan ×2
- Antoine Chaffin
- Carlos Riquelme
- Faisal Ladhak
- Nikhil Pinnaparaju
Cited by
Updated
This page in Markdown → https://md.research.elamur.ai/free/en/authors/nathan-cooper/