--- title: "Ege Erdil — author profile and papers · Evaluation & benchmarks" description: "Ege Erdil: 2 papers on Elamur Research (2024), h-index 4 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/ege-erdil/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ege-erdil/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Ege Erdil # Ege Erdil Ege Erdil has 2 papers in our library, in 2024, most of them on [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Matthew Barnett](https://md.research.elamur.ai/free/en/authors/matthew-barnett/), [Tamay Besiroglu](https://md.research.elamur.ai/free/en/authors/tamay-besiroglu/), [Anson Ho](https://md.research.elamur.ai/free/en/authors/anson-ho/). 2 papers in our library · 2024 [OpenAlex](https://openalex.org/A5046272938) · [**h-index 4**](https://openalex.org/authors/A5046272938) · [11 works](https://openalex.org/works?filter=author.id:A5046272938) · [40 citations](https://openalex.org/works?filter=author.id:A5046272938&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/ege-erdil/#papers) · [🔗 Cited 106 times in our library](https://md.research.elamur.ai/free/en/authors/ege-erdil/cited-by/) · [⭐ Paper Stars ranking: #7650](https://md.research.elamur.ai/free/en/paper-stars/page/77/#star-7650) 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=Ege+Erdil) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ege+Erdil) · [dblp](https://dblp.org/search?q=Ege+Erdil) · [ACL Anthology](https://aclanthology.org/search/?q=Ege+Erdil) ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 7 The field of science this work belongs to (OpenAlex fields).[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/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Language and Linguistics · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Hardware and Architecture · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/hardware-and-architecture/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) 🧭 Topics 2 Research subjects and languages the work is about.[Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) 💡 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 [**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/ege-erdil/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI](https://md.research.elamur.ai/free/en/papers/glazer-2024-frontiermath-benchmark-evaluating-advanced-mathematical/)** *(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. 2. **[Chinchilla Scaling: A replication attempt](https://md.research.elamur.ai/free/en/papers/besiroglu-2024-chinchilla-scaling-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… ## Co-authors here 3 co-authors with a page, the most papers together first. - [Matthew Barnett](https://md.research.elamur.ai/free/en/authors/matthew-barnett/) ×2 - [Tamay Besiroglu](https://md.research.elamur.ai/free/en/authors/tamay-besiroglu/) ×2 - [Anson Ho](https://md.research.elamur.ai/free/en/authors/anson-ho/) ## Cited by Papers of our library cite their works 106 times (of the 149,439 papers whose bibliographies we read); [24 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/ege-erdil/cited-by/). Updated 2 November 2026