---
title: "Beliz Gunel — author profile and papers — Elamur Research"
description: "Beliz Gunel: 2 papers on Elamur Research (2020–2021), h-index 10 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/beliz-gunel/"
---
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# Beliz Gunel

Beliz Gunel has 2 papers in our library, in 2020–2021, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Alexis Conneau](https://md.research.elamur.ai/free/en/authors/alexis-conneau/), [Jingfei Du](https://md.research.elamur.ai/free/en/authors/jingfei-du/), [Edouard Grave](https://md.research.elamur.ai/free/en/authors/edouard-grave/).

2 papers in our library · 2020–2021

[OpenAlex](https://openalex.org/A5067625586) · [ORCID](https://orcid.org/0000-0003-2541-4157) · [**h-index 10**](https://openalex.org/authors/A5067625586) · [33 works](https://openalex.org/works?filter=author.id:A5067625586) · [772 citations](https://openalex.org/works?filter=author.id:A5067625586&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/beliz-gunel/#papers) · [🔗 Cited 224 times in our library](https://md.research.elamur.ai/free/en/authors/beliz-gunel/cited-by/) · [⭐ Paper Stars ranking: #3815](https://md.research.elamur.ai/free/en/paper-stars/page/39/#star-3815)

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=Beliz+Gunel) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Beliz+Gunel) · [dblp](https://dblp.org/search?q=Beliz+Gunel) · [ACL Anthology](https://aclanthology.org/search/?q=Beliz+Gunel)

## Affiliations

[🎓**Stanford University** Stanford · United States 2020–2025 · 10 papers](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🏢**Google** Mountain View · United States 2023–2025 · 6 papers](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**University of California, Berkeley** Berkeley · United States 2015–2018 · 4 papers](https://md.research.elamur.ai/free/en/universities/university-of-california-berkeley/) · [🏢**Google DeepMind** London · United Kingdom 2024–2025 · 3 papers](https://md.research.elamur.ai/free/en/companies/google-deepmind/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed.

## Concepts, shelves and topics

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

📚 Shelves 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/)

🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/)

## Works by year

### 2020s

[**2021** 1 paper Self-training Improves Pre-training for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/du-2021-self-training-improves-pre-training/) · [**2020** 1 paper Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning](https://md.research.elamur.ai/free/en/papers/gunel-2020-supervised-contrastive-learning-pre-trained/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning](https://md.research.elamur.ai/free/en/papers/gunel-2020-supervised-contrastive-learning-pre-trained/)** *(2020 · 216 citations)* Fine-tuning a pre-trained language model with cross-entropy alone tends to generalize poorly when labels are scarce, reacts badly to noisy labels, and produces results that vary a lot between runs.
2. **[Self-training Improves Pre-training for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/du-2021-self-training-improves-pre-training/)** *(2021 · 169 citations)* Self-training uses a teacher model to label unannotated examples for a student model. It usually assumes that unlabeled text from the target task's domain is already available, and that assumption breaks down for many low-resource tasks. The authors ask whether self-training still helps on top of strong…

## Co-authors here

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

- [Alexis Conneau](https://md.research.elamur.ai/free/en/authors/alexis-conneau/) ×2
- [Jingfei Du](https://md.research.elamur.ai/free/en/authors/jingfei-du/) ×2
- [Edouard Grave](https://md.research.elamur.ai/free/en/authors/edouard-grave/)
- [Michael Auli](https://md.research.elamur.ai/free/en/authors/michael-auli/)
- [Onur Celebi](https://md.research.elamur.ai/free/en/authors/onur-celebi/)
- [Ves Stoyanov](https://md.research.elamur.ai/free/en/authors/ves-stoyanov/)
- [Veselin Stoyanov](https://md.research.elamur.ai/free/en/authors/veselin-stoyanov/)
- [Vishrav Chaudhary](https://md.research.elamur.ai/free/en/authors/vishrav-chaudhary/)

## Venues

Where their works here were published, the most works first, with the editions of those that have a page.

- [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/): [NAACL 2021](https://md.research.elamur.ai/free/en/venues/naacl/2021/)

## Cited by

Papers of our library cite their works 224 times (of the 141,840 papers whose bibliographies we read); [14 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/beliz-gunel/cited-by/).

Updated 24 October 2026
