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Luc Pommeret

Luc Pommeret has 2 papers in our library, in 2026, most of them on Dependency parsing, Universal Dependencies, Latin; often with Patrick Paroubek, Thomas Gerald.

2 papers in our library · 2026

OpenAlex · h-index 1 · 11 works · 1 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1 time in our library · ⭐ Paper Stars ranking: #11588

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

🔬Laboratoire Interdisciplinaire des Sciences du NumériqueGif-sur-Yvette · France2025–2026 · 10 paperscurrent🎓Université Paris-SaclayGif-sur-Yvette · France2026 · 8 paperscurrent🔬Centre National de la Recherche ScientifiqueParis · France2026 · 7 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 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 · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksHistory · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Dependency parsing · 1 workLatin · 1 workUniversal Dependencies · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. THIVLVC: Retrieval Augmented Dependency Parsing for Latin (2026 · 1 citation)
    THIVLVC was built to take part in EvaLatin 2026's dependency parsing challenge. The task covers two genres: Seneca's poetry and Thomas Aquinas's philosophical prose. Supervised parsers tend to copy whatever annotation habits their training treebanks contain, so the authors instead let a large language model correct a…
  2. LLM-based Atomic Propositions Help Weak Extractors: Evaluation of a Propositioner for Triplet Extraction (2026)
    Building knowledge graphs from text requires pulling (subject, relation, object) triplets out of dense sentences.

 Co-authors here

2 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 1 time (of the 149,439 papers whose bibliographies we read).

Updated

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