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Florin Cuconasu

Florin Cuconasu has 3 papers in our library, in 2024–2026, most of them on Information retrieval & search, Language models & pretraining, Evaluation & benchmarks; often with Simone Filice, Fabrizio Silvestri, Giovanni Trappolini.

3 papers in our library · 2024–2026

OpenAlex · ORCID · Wikidata · h-index 3 · 14 works · 239 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 111 times in our library · ⭐ Paper Stars ranking: #4730

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

🎓Sapienza University of RomeRome · Italy2023–2026 · 12 paperscurrent🔬Technology Innovation InstituteAbu Dhabi · United Arab Emirates2025–2026 · 4 paperscurrent

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).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksInformation Systems · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Information retrieval & search · 2 worksEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Retrieval-augmented generation · 1 work

 Works by year

2020s

20261 paper20251 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. The Power of Noise: Redefining Retrieval for RAG Systems (2024 · 312 citations)
    Retrieval-Augmented Generation (RAG) supplies an LLM with passages from an IR system so it can answer questions beyond its pre-trained knowledge.
  2. The Distracting Effect: Understanding Irrelevant Passages in RAG (2025 · 21 citations)
    This paper examines a familiar weakness of Retrieval Augmented Generation: passages that do not answer a question but are topically close to it can lead the generating LLM to a wrong answer.
  3. Redefining Retrieval Evaluation in the Era of LLMs (2026 · 1 citation)
    Classic retrieval metrics such as nDCG, MAP and MRR were built for people who read result lists from the top down.

 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 111 times (of the 149,439 papers whose bibliographies we read); 24 citing papers with a page here →.

Updated

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