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Mohammad Gheshlaghi Azar

Mohammad Gheshlaghi Azar has 2 papers in our library, in 2023; often with Daniele Calandriello, Mark Rowland, Michal Valko.

2 papers in our library · 2023

OpenAlex · h-index 21 · 72 works · 7,051 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 560 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #5773

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

🏢Google DeepMindLondon · United Kingdom2017–2023 · 9 papers🎓Northwestern UniversityEvanston · United States2014–2021 · 8 papers🎓Carnegie Mellon UniversityPittsburgh · United States2013 · 4 papers🎓Radboud University NijmegenNijmegen · Netherlands2010–2013 · 4 papers🏢GoogleMountain View · United States2017–2019 · 3 papers🏥Shirley Ryan AbilityLabChicago · United States2014–2017 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksDecision Sciences · 1 workManagement Science and Operations Research · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work

 Works by year

2020s

20232 papers

 Papers

The most cited first (OpenAlex and our library).

  1. A General Theoretical Paradigm to Understand Learning from Human Preferences (2023 · 263 citations)
    This paper by researchers at Google DeepMind provides a theoretical foundation for methods that train language models from human preferences.
  2. Nash Learning from Human Feedback (2023 · 32 citations)
    Standard RLHF reduces pairwise human judgments to a scalar reward, typically through a Bradley-Terry model, and then optimizes the LLM against that score.

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. Bootstrap your own latent: A new approach to self-supervised Learning ↗arXiv (Cornell University) · no summary yetJean-Bastien Grill et al.2020 · 3,531 citations
  2. Noisy Networks for Exploration ↗arXiv (Cornell University) · no summary yetMeire Fortunato et al.2017 · 570 citations
  3. A General Theoretical Paradigm to Understand Learning from Human PreferencesarXiv:2310.12036Mohammad Gheshlaghi Azar, Mark Rowland, Bilal Piot, et al.2023 · 263 citations
  4. Nash Learning from Human FeedbackarXiv:2312.00886Remi Munos, Michal Valko, Daniele Calandriello, et al.2023 · 32 citations

 Co-authors here

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

 Cited by

Papers of our library cite their works 560 times (of the 149,439 papers whose bibliographies we read); 94 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/mohammad-gheshlaghi-azar/