---
title: "Fernando López · Telefónica — author profile and papers"
description: "Fernando López, Telefónica: 2 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who cites them in our library."
canonical: "https://research.elamur.ai/free/en/authors/fernando-lopez/"
---
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# Fernando López

Fernando López has 2 papers in our library, in 2026, most of them on [Question answering](https://md.research.elamur.ai/free/en/topics/question-answering/), [Speech & spoken language](https://md.research.elamur.ai/free/en/topics/speech/); often with [Jordi Luque](https://md.research.elamur.ai/free/en/authors/jordi-luque/), [Ramani Duraiswami](https://md.research.elamur.ai/free/en/authors/ramani-duraiswami/).

2 papers in our library · 2026

[OpenAlex](https://openalex.org/A5125724817) · [**h-index 0**](https://openalex.org/authors/A5125724817) · [5 works](https://openalex.org/works?filter=author.id:A5125724817) · [0 citations](https://openalex.org/works?filter=author.id:A5125724817&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/fernando-lopez/#papers) · [⭐ Paper Stars ranking: #11984](https://md.research.elamur.ai/free/en/paper-stars/page/120/#star-11984)

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=Fernando+L%C3%B3pez) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Fernando+L%C3%B3pez) · [dblp](https://dblp.org/search?q=Fernando+L%C3%B3pez) · [ACL Anthology](https://aclanthology.org/search/?q=Fernando+L%C3%B3pez)

## Affiliations

[🎓**Universidad Autónoma de Madrid** Madrid · Spain 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/universidad-autonoma-de-madrid/) · [🏢**Telefónica** Madrid · Spain 2026 · 1 paper*current*](https://ror.org/012f7tj07) · [🏢**Telefónica Innovación Digital** Madrid 2026 · 1 paper*current*](https://ror.org/03t5r9r41)

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 7 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/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Safety Research · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/)

🧭 Topics 2 Research subjects and languages the work is about.[Question answering · 1 work](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Speech & spoken language · 1 work](https://md.research.elamur.ai/free/en/topics/speech/)

## Works by year

### 2020s

[**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/fernando-lopez/year/2026/)

## Papers

The most cited first (OpenAlex and our library).

1. **[ORCA: Open-ended Response Correctness Assessment for Audio Question Answering](https://md.research.elamur.ai/free/en/papers/sedlacek-2026-orca-open-ended-response-correctness/)** *(2026)* Large audio language models (LALMs) are usually tested with multiple-choice questions, even though free-form answers better reflect real use.
2. **[“OK Aura, Be Fair with Me”: Demographics-Agnostic Training for Bias Mitigation in Wake-up Word Detection](https://md.research.elamur.ai/free/en/papers/lopez-2026-ok-aura-be-fair-me/)** *(2026)* Wake-up Word (WuW) detectors are the always-on entry point to voice assistants. Their decisions rest on very short audio snippets, so they can treat speakers of different sex, age, and accent unequally, forcing some users to repeat the trigger phrase more often. Most bias-mitigation methods need demographic labels…

## Co-authors here

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

- [Jordi Luque](https://md.research.elamur.ai/free/en/authors/jordi-luque/)
- [Ramani Duraiswami](https://md.research.elamur.ai/free/en/authors/ramani-duraiswami/)

## Venues

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

- [Speech Language Models in Low-Resource Settings: Performance, Evaluation, and Bias Analysis (SPEAKABLE) @ LREC](https://md.research.elamur.ai/free/en/venues/speakable/): [Speech Language Models in Low-Resource Settings: Performance, Evaluation, and Bias Analysis (SPEAKABLE) @ LREC 2026](https://md.research.elamur.ai/free/en/venues/speakable/2026/)
- [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/): [Transactions of the Association for Computational Linguistics (TACL) 2026](https://md.research.elamur.ai/free/en/venues/tacl/2026/)

Updated 1 November 2026
