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Timothee Mickus

Timothee Mickus has 3 papers in our library, in 2022–2026, most of them on Language models & pretraining; often with Denis Paperno, Mathieu Constant, Aman Sinha.

3 papers in our library · 2022–2026

OpenAlex · ORCID · h-index 6 · 82 works · 153 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 56 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6971

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

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 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 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 works

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Lexicography · 1 work

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. Semeval-2022 Task 1: CODWOE – Comparing Dictionaries and Word Embeddings (2022 · 59 citations)
    The paper describes the CODWOE shared task at SemEval-2022. It tests whether word embeddings contain the same information as dictionary definitions. The task is divided into two tracks. In the Definition Modeling track, a definition must be generated from a word's vector. In the Reverse Dictionary track, the…
  2. How to Dissect a Muppet: The Structure of Transformer Embedding Spaces (2022 · 31 citations)
    Studies of pretrained Transformer embeddings usually either inspect attention weights or treat the whole network as an opaque box.
  3. Language Models Learn Universal Representations of Numbers and Here's Why You Should Care (2026)
    The paper asks how consistently large language models encode numbers. Earlier studies found sine-like number embeddings but did not measure how closely they match across models, and they did not use natural-language contexts. The authors examine eight open checkpoints from the OLMo 2, Llama 3 and Phi 4 families. They…

All works

4 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. Génération automatique de définitions pour le français (Definition Modeling in French) ↗Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 2 : Traitement Automatique des Langues Naturelles · no summary yetTimothee Mickus, Mathieu Constant, Denis Paperno2020 · 2 citations

 Co-authors here

7 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 56 times (of the 149,439 papers whose bibliographies we read); 17 citing papers with a page here →.

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