In English:

  • Marzena Karpinska and Mohit Iyyer (2023). "Large language models effectively leverage document-level context for literary translation, but critical errors persist"
    Proceedings of the Eighth Conference on Machine Translation [PDF]
  • Kalpesh Krishna, Yixiao Song, Marzena Karpinska, John Wieting, Mohit Iyyer (2023). "Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense"
    Accepted to NeurIPS 2023 [PDF]
  • Anna Rogers, Marzena Karpinska, Jordan Boyd-Graber, Naoaki Okazaki (2023). "Program Chairs’ Report on Peer Review at ACL 2023"
    Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), xl–lxxv. [PDF]
  • Marzena Karpinska, Nishant Raj, Katherine Thai, Yixiao Song, Ankita Gupta and Mohit Iyyer (2022). "DEMETR: Diagnosing Evaluation Metrics for Translation"
    Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing [PDF]
  • Katherine Thai*, Marzena Karpinska*, Kalpesh Krishna, William Ray, Moira Inghilleri, John Wieting and Mohit Iyyer (2022). "Exploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literature"
    Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing [PDF] * equal contributions
  • Ankita Gupta, Marzena Karpinska, Wenlong Zhao, Kalpesh Krishna, Jack Merullo, Luke Yeh, Mohit Iyyer and Brendan O'Connor (2022). "ezCoref: Towards Unifying Annotation Guidelines for Coreference Resolution"
    Findings of the Association for Computational Linguistics: EACL 2023 [PDF]
  • Yoshifumi Kawasaki, Maëlys Salingre, Marzena Karpinska, Hiroya Takamura, and Ryo Nagata (2022). "Revisiting Statistical Laws of Semantic Shift in Romance Cognates"
    The 29th International Conference on Computational Linguistics [PDF]
  • Marzena Karpinska, Nader Akoury, and Mohit Iyyer (2021). "The Perils of Using Mechanical Turk to Evaluate Open-Ended Text Generation"
    Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing [PDF]
  • Marzena Karpinska (2019). “How accented do Caucasian-looking vs. Asian-looking native speakers sound to a Japanese listener?”
    Proceedings of the The International Congress of Phonetic Sciences. Melbourne, Australia: ICPhS, pp. 3691–3695. [PDF]
  • Marzena Karpinska, Paula Kurzawska, and Katarzyna Rozanska (2019). “Digital Lingua Franca or a Culture-Specific Product Leading to Misunderstandings?”
    Emoticons, Kaomoji, and Emoji: The Transformation of Communication in the Digital Age (Routledge Research in Language and Communication). Ed. by E. Giannoulis and Lukas R.A. Wilde. Routledge. Chap. 4 [BOOK]
  • Kimie Yamamura, Ryo Gakutani, Marzena Karpinska , Tetsuro Tanojiri, and Tom Gally (2019). "The Discourse of Kyōyō and English Education in Japan" Komaba Journal of English Education. Department of English Language, The University of Tokyo, Komaba. [PDF]
  • Marzena Karpinska, Bofang Li, Anna Rogers, and Aleksandr Drozd (2018). “Subcharacter Information in Japanese Embeddings: When Is It Worth It?”
    Proceedings of the Workshop on the Relevance of Linguistic Structure in Neural Architectures for NLP. Melbourne, Australia: ACL, pp. 28–37. [PDF]
  • Marzena Karpinska, Shodai Uchida, and Izabelle Grenon (2015). “Vowel perception by listeners from different English dialects”.
    Proceedings of the The International Congress of Phonetic Sciences. Glasgow, Scotland: ICPhS. [PDF]

In Japanese:

  • Kawasaki Yoshifumi, Maëlys Salingre, Marzena Karpinska, Takamura Hiroya, Nagata Ryo (2022). 分散表現を用いたロマンス語同源語動詞の意味変化の分析 (Analysis of Semantic Shift in Romance Cognate Verbs Using Word Embeddings)
    Proceedings of the 28th Annual Conference of the Association for Natural Language Processing. Hamamatsu, Japan. [PDF] (committee award for novelty)