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Ekin Akyürek

Ekin Akyürek has 2 papers in our library, in 2022–2023, most of them on Language models & pretraining; often with Ashwin Kalyan, Dale Schuurmans, Denny Zhou.

2 papers in our library · 2022–2023

OpenAlex · ORCID · Wikidata · h-index 11 · 30 works · 458 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 514 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #4138

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

🎓Massachusetts Institute of TechnologyCambridge · United States2020–2025 · 19 papersEmploymentcurrent🔬MIT Computer Science and Artificial Intelligence LaboratoryCambridge · United States2022–2024 · 3 papers🎓Boston UniversityBoston · United States2023–2024 · 2 papers🏢GoogleMountain View · United States2022 · 2 papers

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

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

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

 Works by year

2020s

20231 paperRL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs20221 paperWhat learning algorithm is in-context learning? Investigations with linear models

 Papers

The most cited first (OpenAlex and our library).

  1. What learning algorithm is in-context learning? Investigations with linear models (2022 · 225 citations)
    This paper asks how transformers manage in-context learning (ICL), meaning how they produce accurate predictions from labeled examples in the prompt without any weight updates.
  2. RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs (2023 · 87 citations)
    Large language models still make errors, and natural language critiques can help them fix their outputs. Human critiques are costly and too slow for online use. Earlier learned critique generators also assumed the downstream model could be fine-tuned, which is not possible for closed models like GPT-3 or ChatGPT.…

All works

4 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. What learning algorithm is in-context learning? Investigations with linear modelsarXiv:2211.15661Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.2022 · 225 citations
  2. Pre-Trained Language Models for Interactive Decision-MakingarXiv:2202.01771 · original ↗ · no summary yetShuang Li et al.2022 · 119 citations
  3. RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model OutputsAnnual Meeting of the Association for Computational Linguistics (ACL)Afra Feyza Akyurek, Ekin Akyurek, Ashwin Kalyan, et al.2023 · 87 citations
  4. The Surprising Effectiveness of Test-Time Training for Few-Shot LearningarXiv:2411.07279 · original ↗ · no summary yetEkin Akyürek et al.2024 · 32 citations

 Co-authors here

8 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 514 times (of the 141,840 papers whose bibliographies we read); 57 citing papers with a page here →.

Updated

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