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Alkis Koudounas

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

2 papers in our library · 2026

OpenAlex · ORCID · h-index 6 · 56 works · 128 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 17 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #9607

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

🎓Politecnico di TorinoTurin · Italy2020–2026 · 39 papersEmployment 2022–2026 · Ph.D. | Researcher, DAUINcurrent🏢SonyTokyo · Japan2026 · 2 papersEmployment since 2026 · Sr. Research Engineer, Speech & Language AIcurrent

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…

All works

5 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. FAME: Fictional Actors for Multilingual ErasureLanguage Resources and Evaluation Conference (LREC)Claudio Savelli, Moreno La Quatra, Alkis Koudounas, et al.2026 · 7 citations
  2. PoliToHFI at SemEval-2023 Task 6: Leveraging Entity-Aware and Hierarchical Transformers For Legal Entity Recognition and Court Judgment Prediction ↗Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023) · no summary yetIrene Benedetto et al.2023 · 7 citations
  3. SVELA at EVALITA 2026: Overview of the Selective Verification of Erasure from LLM Answers TaskEvaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final WorkshopClaudio Savelli, Moreno La Quatra, Alkis Koudounas, et al.2026 · 6 citations
  4. MAINDZ at SemEval-2024 Task 5: CLUEDO - Choosing Legal oUtcome by Explaining Decision through Oversight ↗Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024) · no summary yetIrene Benedetto et al.2024 · 2 citations
  5. Benchmarking Speech-to-Speech Translation Models ↗arXiv:2606.03241 · no summary yetAlkis Koudounas et al.2026

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

Updated

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