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Imanol Schlag

Imanol Schlag has 2 papers in our library, in 2021–2022, most of them on Language models & pretraining, Reasoning; often with Aitor Lewkowycz, Ambrose Slone, Anders Andreassen.

2 papers in our library · 2021–2022

OpenAlex · h-index 10 · 43 works · 572 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 888 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #2531

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

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓ETH ZurichZurich · Switzerland2023–2026 · 16 paperscurrent🔬CSCS - Swiss National Supercomputing CentreLugano2026 · 1 papercurrent🔬Dalle Molle Institute for Artificial Intelligence ResearchLugano · Switzerland2018–2025 · 7 papers🎓University of Applied Sciences and Arts of Southern SwitzerlandManno · Switzerland2020–2021 · 3 papers🎓Università della Svizzera italianaLugano · Switzerland2020–2021 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksApplied Mathematics · 1 workMathematics · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20221 paper20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Solving Quantitative Reasoning Problems with Language Models (2022 · 992 citations)
    Large language models handle many language tasks well but have struggled with quantitative problems in mathematics, science and engineering, where a solver must understand a word problem, recall relevant knowledge and carry out exact symbolic and numerical steps.
  2. Linear Transformers Are Secretly Fast Weight Programmers (2021 · 111 citations)
    The paper shows that linear Transformers, which replace softmax attention with a kernel-based approximation, are mathematically the same as the outer-product Fast Weight Programmers (FWPs) Schmidhuber proposed in the early 1990s, apart from a normalisation term.

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Solving Quantitative Reasoning Problems with Language ModelsConference on Neural Information Processing Systems (NeurIPS)Aitor Lewkowycz, Anders Andreassen, David Dohan, et al.2022 · 992 citations
  2. Linear Transformers Are Secretly Fast Weight ProgrammersarXiv:2102.11174Imanol Schlag, Kazuki Irie, Jurgen Schmidhuber2021 · 111 citations
  3. Large Language Model Programs ↗arXiv:2305.05364 · no summary yetImanol Schlag et al.2023 · 18 citations

 Co-authors here

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

Venues

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

 Cited by

Papers of our library cite their works 888 times (of the 149,439 papers whose bibliographies we read); 280 citing papers with a page here →.

Updated

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