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Fatih Ilhan

Fatih Ilhan has 2 papers in our library, in 2026, most of them on Language models & pretraining, Bias, fairness & safety, Efficient models & compression; often with Fartash Faghri, Ling Liu, Mehrdad Farajtabar.

2 papers in our library · 2026

OpenAlex · ORCID · Wikidata · h-index 9 · 42 works · 279 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 8 times in our library · ⭐ Paper Stars ranking: #12253

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

🎓Georgia Institute of TechnologyAtlanta · United States2023–2026 · 16 paperscurrent🎓Bilkent UniversityAnkara · Türkiye2020–2023 · 6 papers🏢ODTÜ Teknokent (Turkey)Ankara · Türkiye2021–2023 · 2 papers

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

 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 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Efficient models & compression · 1 workBias, fairness & safety · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Unmasking On-Policy Distillation: Where It Helps, Where It Hurts, and Why (2026 · 7 citations)
    On-policy distillation gives a student model dense, per-token supervision, either from a larger external teacher or from the student itself conditioned on privileged context such as a correct solution.
  2. H3Fusion: Helpful, Harmless, Honest Fusion of Aligned LLMs (2026 · 1 citation)
    Aligning an LLM to be helpful, harmless and honest (HHH) at once is difficult. Tuning for one property often hurts another: safety tuning can make a model overly cautious, and pushing helpfulness can increase hallucinations. H3Fusion addresses this by merging three separately aligned copies of one base model into a…

 Co-authors here

6 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 8 times (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated

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