Lina Conti

PhD Student

    Short bio

    Lina Conti is a PhD student at the Fondazione Bruno Kessler and the University of Trento (Italy), specializing in the interpretability of multilingual and multimodal foundation models for translation.

    She holds a master's degree in Computational Linguistics from Université Paris Cité (France) and bachelor's degrees in Computer Science and in Philosophy from Sorbonne University (France).

    Research topics


    • interpretability

    • machine translation

    • language models

    Publications

    1. Conti, Lina; Wisniewski, Guillaume,
      Using Artificial French Data to Understand the Emergence of Gender Bias in Transformer Language Models,
      Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing,
      2023
      , pp. 10362-
      10371

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    #MachineTranslation Research Unit @FBK_research. #nlproc #deeplearning #ai

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    Avatar AILC_NLP @ailc_nlp ·
    30 Jun

    Emanuele Pianta Award for the Best Master’s Thesis in Computational Linguistics submitted at an Italian university and defended between August 1st 2024 and July 31st 2025
    - Deadline: August 1st, 2025 (11:59 pm CEST)
    - All details online: https://clic2025.unica.it/emanuele-pianta-award-for-the-best-masters-thesis/

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    Avatar Fondazione Bruno Kessler - FBK @fbk_research ·
    10 Jun

    Cosa chiedono davvero gli italiani all’intelligenza artificiale?
    FBK in collaborazione con RiTA lancia un’indagine aperta a tutte/i per capire usi reali, abitudini e bisogni.

    Bastano 10 minuti per partecipare, scopri di più: https://magazine.fbk.eu/it/news/italiani-e-ia-cosa-chiediamo-veramente-allintelligenza-artificiale/

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    Avatar Marco Gaido @mgaido91 ·
    11 Jun

    🚀 Last call for the Model Compression for Machine Translation task at #WMT2025 (co-located with #EMNLP2025)!
    Test data out on June 19 ➡️ 2 weeks for evaluation!
    Can you shrink an LLM and keep translation quality high?
    👉 https://www2.statmt.org/wmt25/model-compression.html #NLP #ML #LLM #ModelCompression

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