Elamur Research⌕
☰
home / authors / Tamay Besiroglu

Tamay Besiroglu

Tamay Besiroglu has 3 papers in our library, in 2022–2024, most of them on Language models & pretraining, Evaluation & benchmarks, Reasoning; often with Anson Ho, Ege Erdil, Matthew Barnett.

3 papers in our library · 2022–2024

OpenAlex · ORCID · Wikidata · h-index 9 · 39 works · 1,991 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 288 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #5438

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

🔬MIT Computer Science and Artificial Intelligence LaboratoryCambridge · United States2022–2026 · 7 paperscurrent🎓Massachusetts Institute of TechnologyCambridge · United States2022–2024 · 11 papers🎓University of CambridgeCambridge · United Kingdom2020 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 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 7The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksArts and Humanities · 2 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 2 worksComputational Theory and Mathematics · 1 workHardware and Architecture · 1 workInformation Systems · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 1 workEvaluation & benchmarks · 1 workReasoning · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Scaling laws · 1 work

 Works by year

2020s

20242 papers20221 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Will we run out of data? Limits of LLM scaling based on human-generated data (2022 · 198 citations)
    Scaling laws push LLM developers toward ever-larger training sets, which raises the question of whether public human-written text will eventually run out.
  2. FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI (2024 · 97 citations)
    Popular math benchmarks such as MATH and GSM8K mostly test high-school or early-undergraduate skills, and leading models now score near the ceiling on them.
  3. Chinchilla Scaling: A replication attempt (2024 · 18 citations)
    Hoffmann et al. (2022), the Chinchilla paper, estimated compute-optimal scaling for language models in three ways. The third, Approach 3, fits a parametric loss L(N, D) = E + A/N^α + B/D^β, where N is parameter count and D is training tokens. Epoch AI researchers checked whether this fit holds up. The original data…

All works

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

  1. Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims ↗arXiv:2004.07213 · no summary yetMiles Brundage et al.2020 · 320 citations
  2. Will we run out of data? Limits of LLM scaling based on human-generated dataarXiv:2211.04325Pablo Villalobos, Anson Ho, Jaime Sevilla, et al.2022 · 198 citations
  3. FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AIarXiv:2411.04872Elliot Glazer, Ege Erdil, Tamay Besiroglu, et al.2024 · 97 citations
  4. International AI Safety Report ↗arXiv (Cornell University) · no summary yetYoshua Bengio et al.2025 · 41 citations
  5. Chinchilla Scaling: A replication attemptarXiv:2404.10102Tamay Besiroglu, Ege Erdil, Matthew Barnett, et al.2024 · 18 citations
  6. International Scientific Report on the Safety of Advanced AI (Interim Report) ↗arXiv (Cornell University) · no summary yetYoshua Bengio et al.2024 · 13 citations

 Co-authors here

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

 Cited by

Papers of our library cite their works 288 times (of the 149,439 papers whose bibliographies we read); 65 citing papers with a page here →.

Updated

↑ back to top

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