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Javier Ferrando

Javier Ferrando has 2 papers in our library, in 2024, most of them on Language models & pretraining, Interpretability; often with Arianna Bisazza, Elena Voita, Gabriele Sarti.

2 papers in our library · 2024

OpenAlex · h-index 7 · 16 works · 115 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 100 times in our library · ⭐ Paper Stars ranking: #7651

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

🎓Universitat Politècnica de CatalunyaBarcelona · Spain2022–2024 · 13 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 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 2Research subjects and languages the work is about.Language models & pretraining · 2 worksInterpretability · 1 work

 Works by year

2020s

20242 papers

 Papers

The most cited first (OpenAlex and our library).

  1. A Primer on the Inner Workings of Transformer-based Language Models (2024 · 72 citations)
    This survey addresses a gap in interpretability research. Insights into how language models work internally have accumulated quickly but remain scattered. Earlier NLP surveys centred mostly on encoder models such as BERT. Ferrando, Sarti, Bisazza and Costa-jussà (UPC, University of Groningen, FAIR Meta) instead give…
  2. Information Flow Routes: Automatically Interpreting Language Models at Scale (2024 · 43 citations)
    Mechanistic interpretability usually finds circuits through activation patching. That approach depends on hand-built prompt templates with contrastive counterparts and needs many forward passes, so it does not scale to large models or arbitrary inputs. Ferrando and Voita represent a Transformer's computation as a…

 Co-authors here

4 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 100 times (of the 149,439 papers whose bibliographies we read); 20 citing papers with a page here →.

Updated

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