---
title: "Ido Galil — author profile and papers — Elamur Research"
description: "Ido Galil, Nvidia: 2 papers on Elamur Research (2024–2025), h-index 3 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/ido-galil/"
---
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# Ido Galil

Ido Galil has 2 papers in our library, in 2024–2025, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Akhiad Bercovich](https://md.research.elamur.ai/free/en/authors/akhiad-bercovich/), [Mohammad Dabbah](https://md.research.elamur.ai/free/en/authors/mohammad-dabbah/), [Tomer Ronen](https://md.research.elamur.ai/free/en/authors/tomer-ronen/).

2 papers in our library · 2024–2025

[OpenAlex](https://openalex.org/A5031244684) · [**h-index 3**](https://openalex.org/authors/A5031244684) · [24 works](https://openalex.org/works?filter=author.id:A5031244684) · [26 citations](https://openalex.org/works?filter=author.id:A5031244684&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/ido-galil/#papers) · [🔗 Cited 83 times in our library](https://md.research.elamur.ai/free/en/authors/ido-galil/cited-by/) · [⭐ Paper Stars ranking: #8722](https://md.research.elamur.ai/free/en/paper-stars/page/88/#star-8722)

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=Ido+Galil) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ido+Galil) · [dblp](https://dblp.org/search?q=Ido+Galil) · [ACL Anthology](https://aclanthology.org/search/?q=Ido+Galil)

## Affiliations

[🎓**Technion – Israel Institute of Technology** Haifa · Israel 2021–2026 · 10 papers*current*](https://md.research.elamur.ai/free/en/universities/technion-israel-institute-of-technology/) · [🏢**Nvidia** Reading · United Kingdom 2025–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/companies/nvidia-united-kingdom/) · [🏢**Nvidia** Santa Clara · United States 2025–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/companies/nvidia/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 5 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/)

🧭 Topics 3 Research subjects and languages the work is about.[Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/)

## Works by year

### 2020s

[**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/ido-galil/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/ido-galil/year/2024/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Llama-Nemotron: Efficient Reasoning Models](https://md.research.elamur.ai/free/en/papers/bercovich-2025-llama-nemotron-efficient-reasoning-models/)** *(2025 · 76 citations)* Reasoning-oriented language models write long chains of thought, so inference cost increasingly limits how useful they are.
2. **[Puzzle: Distillation-Based NAS for Inference-Optimized LLMs](https://md.research.elamur.ai/free/en/papers/bercovich-2024-puzzle-distillation-based-nas-inference/)** *(2024 · 10 citations)* Serving large language models is costly, and standard transformers stack identical layers that suit training stability rather than cheap inference.

## Co-authors here

6 co-authors with a page, the most papers together first.

- [Akhiad Bercovich](https://md.research.elamur.ai/free/en/authors/akhiad-bercovich/) ×2
- [Mohammad Dabbah](https://md.research.elamur.ai/free/en/authors/mohammad-dabbah/) ×2
- [Tomer Ronen](https://md.research.elamur.ai/free/en/authors/tomer-ronen/) ×2
- [Ehud Karpas](https://md.research.elamur.ai/free/en/authors/ehud-karpas/)
- [Itay Levy](https://md.research.elamur.ai/free/en/authors/itay-levy/)
- [Ran El-Yaniv](https://md.research.elamur.ai/free/en/authors/ran-el-yaniv/)

## Cited by

Papers of our library cite their works 83 times (of the 149,439 papers whose bibliographies we read); [35 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/ido-galil/cited-by/).

Updated 3 November 2026
