Alexander Hägele

Alexander Hägele has 2 papers in our library, in 2024–2026, most of them on Language models & pretraining; often with Alejandro Hernández-Cano, Angelika Romanou, Bettina Messmer.

2 papers in our library · 2024–2026

The profile is the library's match of the name; two people with one name are not always told apart.

Affiliations

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

Of its works in our library: the number of works on each and its rating among them.

The most cited first (OpenAlex and our library).

Apertus: Democratizing Open and Compliant LLMs for Global Language Environments (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…
Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations (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.…

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

Where their works here were published, the most works first, with the editions of those that have a page.

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 →.

Updated 24 October 2026