Elamur Research⌕
☰
home / authors / Jordi Luque

Jordi Luque

Jordi Luque has 2 papers in our library, in 2021–2026, most of them on Language models & pretraining, Speech & spoken language, Multilingual & cross-lingual NLP; often with Guillermo Cambara, Mireia Farrus.

2 papers in our library · 2021–2026

OpenAlex · ORCID · h-index 19 · 83 works · 3,814 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #6271

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

🏢TelefónicaMadrid · Spain2020–2026 · 5 paperscurrent🏢Telefonica Research and DevelopmentMadrid · Spain2014–2025 · 38 papers🎓Universitat Politècnica de CatalunyaBarcelona · Spain2006–2012 · 12 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.

 Concepts, shelves and topics

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

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksExperimental and Cognitive Psychology · 1 workPsychology · 1 workSignal Processing · 1 work

🧭 Topics 4Research subjects and languages the work is about.Language models & pretraining · 1 workMultilingual & cross-lingual NLP · 1 workEnglish · 1 workSpeech & spoken language · 1 work

 Works by year

2020s

20261 paperOptimizing Multilingual LLMs via Federated Learning: A Study of Client Language Composition20211 paperEnglish Accent Accuracy Analysis in a State-of-the-Art Automatic Speech Recognition System

 Papers

The most cited first (OpenAlex and our library).

  1. Optimizing Multilingual LLMs via Federated Learning: A Study of Client Language Composition (2026 · 1 citation)
    Federated learning (FL) of multilingual LLMs is difficult when clients hold text in different languages. These non-IID splits cause client drift and tend to disadvantage languages with fewer resources. The authors study how the language mix inside each client's local data affects global model quality, cross-lingual…
  2. English Accent Accuracy Analysis in a State-of-the-Art Automatic Speech Recognition System (2021)
    The paper asks whether a modern, heavily trained speech recognizer still performs unevenly across English accents.

 Co-authors here

2 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.

Updated

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