🧑‍🔬 Who cites Nam Soo Kim

85 citations of their works from 81 papers of our library (of the 141,840 whose bibliographies we read) · 14 with a page here, the most cited first · ← Nam Soo Kim

1. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,703 citations
   Language (Technology) is Power: A Critical Survey of “Bias” in NLPAnnual Meeting of the Association for Computational Linguistics (ACL)Su Lin Blodgett, Solon Barocas, Hal Daumé III, et al.2020 · 1,703 citations
   Gender Bias in Machine TranslationTransactions of the Association for Computational Linguistics (TACL)Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, et al.2021 · 310 citations
2. Towards Understanding and Mitigating Social Biases in Language ModelsarXiv:2106.13219Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, et al.2021 · 265 citations
   Societal Biases in Language Generation: Progress and ChallengesAnnual Meeting of the Association for Computational Linguistics (ACL)Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al.2021 · 253 citations
   UNQOVERing Stereotyping Biases via Underspecified QuestionsFindings of the Association for Computational LinguisticsTao Li, Daniel Khashabi, Tushar Khot, et al.2020 · 145 citations
   Gender in Danger? Evaluating Speech Translation Technology on the MuST-SHE CorpusAnnual Meeting of the Association for Computational Linguistics (ACL)Luisa Bentivogli, Beatrice Savoldi, Matteo Negri, et al.2020 · 100 citations
   Inseq: An Interpretability Toolkit for Sequence Generation ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Gabriele Sarti, Nils Feldhus, Ludwig Sickert, et al.2023 · 96 citations
   Gender Bias Evaluation in Machine Translation for Amharic, Tigrigna, and Afaan OromooWorkshop on Gender-Inclusive Translation TechnologiesWalelign Sewunetie, Atnafu Tonja, Tadesse Belay, et al.2024 · 5 citations
   Uncertainty Quantification for Evaluating Gender Bias in Machine TranslationFindings of the Association for Computational LinguisticsIeva Staliunaite, Julius Cheng, Andreas Vlachos2026 · 1 citation
   A Chinese Challenge Set to Assess Gender Bias in Automated TranslationWorkshop on Gender-Inclusive Translation TechnologiesXiaolan Xu, Sara Mendes, Yu-Yin Hsu2026
   ConGA: Guidelines for Contextual Gender Annotation. a Framework for Annotating Gender in Machine TranslationLanguage Resources and Evaluation Conference (LREC)Argentina Anna Rescigno, Eva Vanmassenhove, Johanna Monti2026
   Rethinking Gender Annotation for Bias Evaluation in Machine Translation: Can LLMs Improve Reliability?Workshop on Gender-Inclusive Translation TechnologiesChiara Manna, Argentina Anna Rescigno, Eva Vanmassenhove2026
   Yeswa-Stories: A Three-Way Parallel Dataset of Female African Figures in Low-Web Data LanguagesWorkshop on Gender-Inclusive Translation TechnologiesBethelhem Mamo, Hellina Nigatu2026

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