--- title: "Who cites Nam Soo Kim — 81 papers of our library" description: "81 papers of the Elamur Research library cite the works of Nam Soo Kim, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/nam-soo-kim/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/nam-soo-kim/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Nam Soo Kim](https://md.research.elamur.ai/free/en/authors/nam-soo-kim/) / cited by # 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](https://md.research.elamur.ai/free/en/authors/nam-soo-kim/) 1. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,703 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/) 2. **[Language (Technology) is Power: A Critical Survey of “Bias” in NLP](https://md.research.elamur.ai/free/en/papers/blodgett-2020-language-technology-is-power-critical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Su Lin Blodgett, Solon Barocas, Hal Daumé III, et al.*2020 · 1,703 citations* 3. **[Gender Bias in Machine Translation](https://md.research.elamur.ai/free/en/papers/savoldi-2021-gender-bias-machine-translation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, et al.*2021 · 310 citations* 4. [**Towards Understanding and Mitigating Social Biases in Language Models arXiv:2106.13219**Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, et al.*2021 · 265 citations*](https://md.research.elamur.ai/free/en/papers/liang-2021-towards-understanding-mitigating-social-biases/) 5. **[Societal Biases in Language Generation: Progress and Challenges](https://md.research.elamur.ai/free/en/papers/sheng-2021-societal-biases-language-generation-progress/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al.*2021 · 253 citations* 6. **[UNQOVERing Stereotyping Biases via Underspecified Questions](https://md.research.elamur.ai/free/en/papers/li-2020-unqovering-stereotyping-biases-underspecified-questions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tao Li, Daniel Khashabi, Tushar Khot, et al.*2020 · 145 citations* 7. **[Gender in Danger? Evaluating Speech Translation Technology on the MuST-SHE Corpus](https://md.research.elamur.ai/free/en/papers/bentivogli-2020-gender-danger-evaluating-speech-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luisa Bentivogli, Beatrice Savoldi, Matteo Negri, et al.*2020 · 100 citations* 8. **[Inseq: An Interpretability Toolkit for Sequence Generation Models](https://md.research.elamur.ai/free/en/papers/sarti-2023-inseq-interpretability-toolkit-sequence-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gabriele Sarti, Nils Feldhus, Ludwig Sickert, et al.*2023 · 96 citations* 9. **[Gender Bias Evaluation in Machine Translation for Amharic, Tigrigna, and Afaan Oromoo](https://md.research.elamur.ai/free/en/papers/sewunetie-2024-gender-bias-evaluation-machine-translation/) [Workshop on Gender-Inclusive Translation Technologies](https://md.research.elamur.ai/free/en/venues/gitt/)**Walelign Sewunetie, Atnafu Tonja, Tadesse Belay, et al.*2024 · 5 citations* 10. **[Uncertainty Quantification for Evaluating Gender Bias in Machine Translation](https://md.research.elamur.ai/free/en/papers/staliunaite-2026-uncertainty-quantification-evaluating-gender-bias/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ieva Staliunaite, Julius Cheng, Andreas Vlachos*2026 · 1 citation* 11. **[A Chinese Challenge Set to Assess Gender Bias in Automated Translation](https://md.research.elamur.ai/free/en/papers/xu-2026-chinese-challenge-set-assess-gender/) [Workshop on Gender-Inclusive Translation Technologies](https://md.research.elamur.ai/free/en/venues/gitt/)**Xiaolan Xu, Sara Mendes, Yu-Yin Hsu*2026* 12. **[ConGA: Guidelines for Contextual Gender Annotation. a Framework for Annotating Gender in Machine Translation](https://md.research.elamur.ai/free/en/papers/rescigno-2026-conga-guidelines-contextual-gender-annotation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Argentina Anna Rescigno, Eva Vanmassenhove, Johanna Monti*2026* 13. **[Rethinking Gender Annotation for Bias Evaluation in Machine Translation: Can LLMs Improve Reliability?](https://md.research.elamur.ai/free/en/papers/manna-2026-rethinking-gender-annotation-bias-evaluation/) [Workshop on Gender-Inclusive Translation Technologies](https://md.research.elamur.ai/free/en/venues/gitt/)**Chiara Manna, Argentina Anna Rescigno, Eva Vanmassenhove*2026* 14. **[Yeswa-Stories: A Three-Way Parallel Dataset of Female African Figures in Low-Web Data Languages](https://md.research.elamur.ai/free/en/papers/mamo-2026-yeswa-stories-three-way-parallel/) [Workshop on Gender-Inclusive Translation Technologies](https://md.research.elamur.ai/free/en/venues/gitt/)**Bethelhem Mamo, Hellina Nigatu*2026* 67 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/nam-soo-kim/) — Nam Soo Kim