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Moreno La Quatra

Moreno La Quatra has 2 papers in our library, in 2026, most of them on Language models & pretraining, Multilingual & cross-lingual NLP, Evaluation & benchmarks; often with Alkis Koudounas, Claudio Savelli, Flavio Giobergia.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 11 · 59 works · 431 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 12 times in our library · ⭐ Paper Stars ranking: #9631

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

🎓Università degli Studi di Enna KoreEnna · Italy2022–2026 · 28 paperscurrent🎓Politecnico di TorinoTurin · Italy2019–2023 · 22 papers

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 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksSafety Research · 1 workSocial Sciences · 1 work

🧭 Topics 3Research subjects and languages the work is about.Multilingual & cross-lingual NLP · 1 workEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. FAME: Fictional Actors for Multilingual Erasure (2026 · 7 citations)
    Machine Unlearning methods remove specific knowledge from a trained LLM without retraining it, which is relevant to privacy rights such as GDPR erasure requests.
  2. SVELA at EVALITA 2026: Overview of the Selective Verification of Erasure from LLM Answers Task (2026 · 6 citations)
    SVELA, a shared task at EVALITA 2026, addresses how to audit machine unlearning. The question is whether a Large Language Model that has been through an unlearning procedure has actually lost targeted knowledge, which matters for GDPR-style deletion requests. The organizers fine-tuned LLMs on synthetic actor…

 Co-authors here

3 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 12 times (of the 149,439 papers whose bibliographies we read); 5 citing papers with a page here →.

Updated

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