--- title: "Tim Dettmers — author profile and papers" description: "Tim Dettmers, Allen Institute for Artificial Intelligence: 2 papers on Elamur Research (2021–2022), h-index 16 — affiliations, topics, co-authors and who…" canonical: "https://research.elamur.ai/free/en/authors/tim-dettmers/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/tim-dettmers/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Tim Dettmers # Tim Dettmers Tim Dettmers has 2 papers in our library, in 2021–2022, most of them on [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Luke Zettlemoyer](https://md.research.elamur.ai/free/en/authors/luke-zettlemoyer/), [Mike Lewis](https://md.research.elamur.ai/free/en/authors/mike-lewis/), [Sam Shleifer](https://md.research.elamur.ai/free/en/authors/sam-shleifer/). 2 papers in our library · 2021–2022 [OpenAlex](https://openalex.org/A5067514564) · [**h-index 16**](https://openalex.org/authors/A5067514564) · [37 works](https://openalex.org/works?filter=author.id:A5067514564) · [6,315 citations](https://openalex.org/works?filter=author.id:A5067514564&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/tim-dettmers/#papers) · [🔗 455 citations in our library](https://md.research.elamur.ai/free/en/authors/tim-dettmers/cited-by/) · [2 more in our library without a page yet](#also) · [⭐ Paper Star rank #3532](https://md.research.elamur.ai/free/en/paper-stars/page/36/#star-3532) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Tim+Dettmers) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Tim+Dettmers) · [dblp](https://dblp.org/search?q=Tim+Dettmers) · [ACL Anthology](https://aclanthology.org/search/?q=Tim+Dettmers) ## Affiliations [🎓**Carnegie Mellon University** Pittsburgh · United States 2026 · 4 papers*current*](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) · [🔬**Allen Institute for Artificial Intelligence** Seattle · United States 2022–2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/labs/allen-institute-for-artificial-intelligence/) · [🎓**University of Washington** Seattle · United States 2020–2023 · 10 papers](https://md.research.elamur.ai/free/en/universities/university-of-washington/) · [🎓**Università della Svizzera italiana** Lugano · Switzerland 2015–2018 · 5 papers](https://md.research.elamur.ai/free/en/universities/universita-della-svizzera-italiana/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed. ## Topics [Efficient models & compression (1)](https://md.research.elamur.ai/free/en/topics/efficient-models/) ## Works by year ### 2020s [**2022** 1 paper](https://md.research.elamur.ai/free/en/papers/dettmers-2022-case-4-bit-precision-k/) · [**2021** 1 paper](https://md.research.elamur.ai/free/en/papers/dettmers-2021-8-bit-optimizers-block-wise/) ## Papers The most cited first (OpenAlex and our library). 1. **[8-bit Optimizers via Block-wise Quantization](https://md.research.elamur.ai/free/en/papers/dettmers-2021-8-bit-optimizers-block-wise/)** *(2021 · 177 citations)* Stateful optimizers such as Adam and SGD with momentum store per-parameter gradient statistics. These statistics take up a large share of training memory (33–75% by the authors' estimate), which limits how big a model can fit on given hardware. Dettmers et al. show that these statistics can be kept in 8 bits instead… 2. **[The case for 4-bit precision: k-bit Inference Scaling Laws](https://md.research.elamur.ai/free/en/papers/dettmers-2022-case-4-bit-precision-k/)** *(2022 · 119 citations)* Quantizing an LLM shrinks its memory use and, at small batch sizes, its latency. This raises a practical question: for a fixed budget of total model bits, is it better to run a larger model at low precision or a smaller one at higher precision? Dettmers and Zettlemoyer frame this as inference scaling laws that relate… ## Also in our library 2 more works of theirs are in our library without a page here yet; they will appear as we publish them. ## Co-authors here 3 co-authors with a page, the most papers together first. - [Luke Zettlemoyer](https://md.research.elamur.ai/free/en/authors/luke-zettlemoyer/) ×2 - [Mike Lewis](https://md.research.elamur.ai/free/en/authors/mike-lewis/) - [Sam Shleifer](https://md.research.elamur.ai/free/en/authors/sam-shleifer/) ## Cited by Papers of our library cite their works 455 times (of the 140,884 papers whose bibliographies we read); [21 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/tim-dettmers/cited-by/).