--- title: "Dan Alistarh — author profile and papers — Elamur Research" description: "Dan Alistarh, Red Hat: 3 papers on Elamur Research (2024–2026), h-index 30 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/dan-alistarh/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/dan-alistarh/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Dan Alistarh # Dan Alistarh Dan Alistarh has 3 papers in our library, in 2024–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Amirkeivan Mohtashami](https://md.research.elamur.ai/free/en/authors/amirkeivan-mohtashami/), [Bo Li](https://md.research.elamur.ai/free/en/authors/bo-li/), [Martin Jaggi](https://md.research.elamur.ai/free/en/authors/martin-jaggi/). 3 papers in our library · 2024–2026 [OpenAlex](https://openalex.org/A5083822059) · [ORCID](https://orcid.org/0000-0003-3650-940X) · [Wikidata](https://www.wikidata.org/wiki/Q102975405) · [**h-index 30**](https://openalex.org/authors/A5083822059) · [321 works](https://openalex.org/works?filter=author.id:A5083822059) · [4,061 citations](https://openalex.org/works?filter=author.id:A5083822059&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/dan-alistarh/#papers) · [🔗 Cited 454 times in our library](https://md.research.elamur.ai/free/en/authors/dan-alistarh/cited-by/) · [5 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #5128](https://md.research.elamur.ai/free/en/paper-stars/page/52/#star-5128) 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=Dan+Alistarh) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Dan+Alistarh) · [dblp](https://dblp.org/search?q=Dan+Alistarh) · [ACL Anthology](https://aclanthology.org/search/?q=Dan+Alistarh) ## Affiliations [🎓**Institute of Science and Technology Austria** Klosterneuburg · Austria 2017–2026 · 172 papersEmployment*current*](https://md.research.elamur.ai/free/en/universities/institute-of-science-and-technology-austria/) · [🏢**Red Hat** Raleigh · United States 2025–2026 · 8 papers*current*](https://ror.org/03ncs3316) · [🎓**Lancaster University** Lancaster · United Kingdom 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/lancaster-university/) · [🏢**Microsoft Research** Cambridge · United Kingdom 2014–2017 · 18 papers](https://md.research.elamur.ai/free/en/companies/microsoft-research-united-kingdom/) · [🎓**École Polytechnique Fédérale de Lausanne** Lausanne · Switzerland 2008–2025 · 17 papersEducation](https://md.research.elamur.ai/free/en/universities/ecole-polytechnique-federale-de-lausanne/) · [🎓**ETH Zurich** Zurich · Switzerland 2013–2020 · 14 papers](https://md.research.elamur.ai/free/en/universities/eth-zurich/) · [🏢**Microsoft** Redmond · United States 2014–2016 · 5 papers](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🎓**Massachusetts Institute of Technology** Cambridge · United States 2013 · 2 papers](https://md.research.elamur.ai/free/en/universities/massachusetts-institute-of-technology/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 more institutions on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 8 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Electrical and Electronic Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/electrical-and-electronic-engineering/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) 🧭 Topics 2 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) ## Works by year ### 2020s [**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/dan-alistarh/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/dan-alistarh/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/dan-alistarh/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs](https://md.research.elamur.ai/free/en/papers/ashkboos-2024-quarot-outlier-free-4-bit/)** *(2024 · 254 citations)* Quantizing large language models to 4 bits is hard because activations contain outliers: individual channels whose values are many times larger than the rest. 2. **[“Give Me BF16 or Give Me Death”? Accuracy-Performance Trade-Offs in LLM Quantization](https://md.research.elamur.ai/free/en/papers/kurtic-2025-give-me-bf16-or-give/)** *(2025 · 21 citations)* Quantization is the most common way to make LLM inference cheaper. However, practitioners lack systematic evidence on how much accuracy each popular format sacrifices and what speed or cost savings it delivers. The authors quantize the whole Llama-3.1 family (8B, 70B, 405B) into three formats with broad hardware… 3. **[Speculative Decoding Speed-of-Light: Optimal Lower Bounds via Branching Random Walks](https://md.research.elamur.ai/free/en/papers/pankratov-2026-speculative-decoding-speed-light-optimal/)** *(2026 · 1 citation)* Speculative decoding speeds up LLM inference. A cheap drafter proposes a sequence or tree of tokens, and the target model checks up to P of them in one parallel pass. It has been unclear how much speedup this approach can deliver in principle. Pankratov and Alistarh derive what they call the first tight limit for any… ## All works 8 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them. 1. **[QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding ↗](https://arxiv.org/abs/1610.02132) arXiv:1610.02132 · no summary yet**Dan Alistarh et al.*2016 · 962 citations* 2. **[QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs](https://md.research.elamur.ai/free/en/papers/ashkboos-2024-quarot-outlier-free-4-bit/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, et al.*2024 · 254 citations* 3. **[The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models ↗](https://aclanthology.org/2022.emnlp-main.279/) Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · no summary yet**Eldar Kurtic et al.*2022 · 115 citations* 4. **[Extreme Compression of Large Language Models via Additive Quantization ↗](https://arxiv.org/abs/2401.06118) ICML 2024 · no summary yet**Vage Egiazarian et al.*2024 · 84 citations* 5. **[“Give Me BF16 or Give Me Death”? Accuracy-Performance Trade-Offs in LLM Quantization](https://md.research.elamur.ai/free/en/papers/kurtic-2025-give-me-bf16-or-give/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eldar Kurtic, Alexandre Noll Marques, Shubhra Pandit, et al.*2025 · 21 citations* 6. **[MLSys: The New Frontier of Machine Learning Systems ↗](https://arxiv.org/abs/1904.03257) arXiv (Cornell University) · no summary yet**Alexander Ratner et al.*2019 · 19 citations* 7. **[Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization ↗](https://arxiv.org/abs/2404.03605) arXiv:2404.03605 · no summary yet**Aniruddha Nrusimha et al.*2024 · 6 citations* 8. **[Speculative Decoding Speed-of-Light: Optimal Lower Bounds via Branching Random Walks](https://md.research.elamur.ai/free/en/papers/pankratov-2026-speculative-decoding-speed-light-optimal/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sergey Pankratov, Dan Alistarh*2026 · 1 citation* ## Co-authors here 3 co-authors with a page, the most papers together first. - [Amirkeivan Mohtashami](https://md.research.elamur.ai/free/en/authors/amirkeivan-mohtashami/) - [Bo Li](https://md.research.elamur.ai/free/en/authors/bo-li/) - [Martin Jaggi](https://md.research.elamur.ai/free/en/authors/martin-jaggi/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) - [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/): [EACL 2026](https://md.research.elamur.ai/free/en/venues/eacl/2026/) - [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/): [NeurIPS 2024](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2024/) - ICML 2024 - Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing ## Cited by Papers of our library cite their works 454 times (of the 149,439 papers whose bibliographies we read); [25 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/dan-alistarh/cited-by/). Updated 31 October 2026