---
title: "Alexander Hägele — author profile and papers in our library"
description: "Alexander Hägele, École Polytechnique Fédérale de Lausanne: 2 papers on Elamur Research (2024–2026), h-index 2 — affiliations, topics…"
canonical: "https://research.elamur.ai/free/en/authors/alexander-hagele/"
---
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# Alexander Hägele

Alexander Hägele has 2 papers in our library, in 2024–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Alejandro Hernández-Cano](https://md.research.elamur.ai/free/en/authors/alejandro-hernandez-cano/), [Angelika Romanou](https://md.research.elamur.ai/free/en/authors/angelika-romanou/), [Bettina Messmer](https://md.research.elamur.ai/free/en/authors/bettina-messmer/).

2 papers in our library · 2024–2026

[OpenAlex](https://openalex.org/A5098954170) · [**h-index 2**](https://openalex.org/authors/A5098954170) · [8 works](https://openalex.org/works?filter=author.id:A5098954170) · [20 citations](https://openalex.org/works?filter=author.id:A5098954170&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/alexander-hagele/#papers) · [🔗 Cited 75 times in our library](https://md.research.elamur.ai/free/en/authors/alexander-hagele/cited-by/) · [⭐ Paper Stars ranking: #5115](https://md.research.elamur.ai/free/en/paper-stars/page/52/#star-5115)

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=Alexander+H%C3%A4gele) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Alexander+H%C3%A4gele) · [dblp](https://dblp.org/search?q=Alexander+H%C3%A4gele) · [ACL Anthology](https://aclanthology.org/search/?q=Alexander+H%C3%A4gele)

## Affiliations

[🎓**École Polytechnique Fédérale de Lausanne** Lausanne · Switzerland 2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/universities/ecole-polytechnique-federale-de-lausanne/)

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 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/)

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

💡 Concepts 1 Key ideas and methods explained on our concept pages.[Scaling laws · 1 work](https://md.research.elamur.ai/free/en/concepts/scaling-laws/)

## Works by year

### 2020s

[**2026** 1 paper Alexander Hägele's papers of 2026](https://md.research.elamur.ai/free/en/papers/cano-2026-apertus-democratizing-open-compliant-llms/) · [**2024** 1 paper Alexander Hägele's papers of 2024](https://md.research.elamur.ai/free/en/papers/hagele-2024-scaling-laws-compute-optimal-training/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Apertus: Democratizing Open and Compliant LLMs for Global Language Environments](https://md.research.elamur.ai/free/en/papers/cano-2026-apertus-democratizing-open-compliant-llms/)** *(2026 · 67 citations)* Most "open" LLMs release only their weights. Their training data stays undisclosed, may ignore content owners' rights, and is heavily skewed toward English and a few high-resource languages. Apertus responds with a fully open suite of 8B and 70B models, both base and Instruct. Pretraining used 15T tokens drawn only…
2. **[Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations](https://md.research.elamur.ai/free/en/papers/hagele-2024-scaling-laws-compute-optimal-training/)** *(2024 · 26 citations)* The paper questions the habit of training large language models with a cosine learning rate schedule. This schedule performs best solely when its cycle is set to equal the full training duration. As a result, the model has to be trained from scratch for every token budget, which makes scaling laws studies expensive.…

## Co-authors here

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

- [Alejandro Hernández-Cano](https://md.research.elamur.ai/free/en/authors/alejandro-hernandez-cano/)
- [Angelika Romanou](https://md.research.elamur.ai/free/en/authors/angelika-romanou/)
- [Bettina Messmer](https://md.research.elamur.ai/free/en/authors/bettina-messmer/)
- [Elie Bakouch](https://md.research.elamur.ai/free/en/authors/elie-bakouch/)
- [Leandro Von Werra](https://md.research.elamur.ai/free/en/authors/leandro-von-werra/)
- [Loubna Ben Allal](https://md.research.elamur.ai/free/en/authors/loubna-ben-allal/)
- [Martin Jaggi](https://md.research.elamur.ai/free/en/authors/martin-jaggi/)
- [Mete Ismayilzada](https://md.research.elamur.ai/free/en/authors/mete-ismayilzada/)

## 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 2026](https://md.research.elamur.ai/free/en/venues/acl/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/)

## Cited by

Papers of our library cite their works 75 times (of the 141,840 papers whose bibliographies we read); [10 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/alexander-hagele/cited-by/).

Updated 24 October 2026
