Papers by Janiça Hackenbuchner

2 papers
Glitter: A Multi-Sentence, Multi-Reference Benchmark for Gender-Fair German Machine Translation (2025.findings-emnlp)

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Challenge: Existing MT models are limited in size and often consist of single sentences or single gender-fair formulation types.
Approach: They propose a benchmark for machine translation that features extended passages with professional translations implementing gender-fair alternatives: neutral rewording, typographical solutions and neologistic forms.
Outcome: The proposed benchmark features extended passages with professional translations implementing three gender-fair alternatives: neutral rewording, typographical solutions (gender star), and neologistic forms (-ens forms).
Mind the Inclusivity Gap: Multilingual Gender-Neutral Translation Evaluation with mGeNTE (2025.emnlp-main)

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Challenge: Genderneutral translation (GNT) is a linguistic strategy towards fairer communication across languages.
Approach: They propose to use a multilingual evaluation resource to evaluate inclusive translation with state-of-the-art instruction-following language models (LMs)
Outcome: The proposed model can recognize when neutrality is appropriate, but cannot consistently produce neutral translations, limiting their usability.

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