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Peter Izsak

Peter Izsak has 2 papers in our library, in 2022–2024, most of them on Language models & pretraining; often with Adi Haviv, Danqi Chen, Howard Yen.

2 papers in our library · 2022–2024

OpenAlex · h-index 7 · 22 works · 647 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 163 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #7188

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

🏢IntelSanta Clara · United States2018–2024 · 8 paperscurrent🎓Princeton UniversityPrinceton · United States2024 · 1 papercurrent🏢IntelKiryat Gat · Israel2018–2023 · 7 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

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

 Works by year

2020s

20241 paper20221 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Transformer Language Models without Positional Encodings Still Learn Positional Information (2022 · 111 citations)
    Self-attention in transformers ignores token order, so language models usually receive explicit position information through embeddings or attention biases.
  2. HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly (2024 · 55 citations)
    Developers of long-context language models (LCLMs) tend to report synthetic needle-in-a-haystack (NIAH) scores or a hand-picked set of datasets.

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. How to Train BERT with an Academic Budget ↗Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · no summary yetPeter Izsak, Moshe Berchansky, Omer Levy2021 · 130 citations
  2. Transformer Language Models without Positional Encodings Still Learn Positional InformationarXiv:2203.16634Adi Haviv, Ori Ram, Ofir Press, et al.2022 · 111 citations
  3. HELMET: How to Evaluate Long-Context Language Models Effectively and ThoroughlyarXiv:2410.02694Howard Yen, Tianyu Gao, Minmin Hou, et al.2024 · 55 citations

 Co-authors here

7 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 163 times (of the 149,439 papers whose bibliographies we read); 36 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/peter-izsak/