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Screening Gender Transfer in Neural Machine Translation

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  • معلومة اضافية
    • Contributors:
      Laboratoire de Linguistique Formelle (LLF - UMR7110); Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité); Centre de Linguistique Inter-langues, de Lexicologie, de Linguistique Anglaise et de Corpus (CLILLAC-ARP (URP_3967)); Université Paris Cité (UPCité); Laboratoire Interdisciplinaire des Sciences du Numérique (LISN); Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS); This work was partially funded by the NeuroViz project subsidized by the Ile-de-France Region, and supported in part by the 2020 émergence research project SPECTRANS.; EMNLP
    • بيانات النشر:
      HAL CCSD
    • الموضوع:
      2021
    • الموضوع:
    • نبذة مختصرة :
      International audience ; This paper aims at identifying the information flow in state-of-the-art machine translation systems, taking as example the transfer of gender when translating from French into English.Using a controlled set of examples, we experiment several ways to investigate how gender information circulates in a encoder-decoder architecture considering both probing techniques as well as interventions on the internal representations used in the MT system. Our results show that gender information can be found in all token representations built by the encoder and the decoder and lead us to conclude that there are multiple pathways for gender transfer.
    • Relation:
      hal-03993451; https://hal.science/hal-03993451; https://hal.science/hal-03993451/document; https://hal.science/hal-03993451/file/Poster_BLACKBOX.pdf
    • Rights:
      http://creativecommons.org/licenses/by/ ; info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.A0C88C5