Awards and accolades

Recent publications

  • Alaçam, Özge, Ronja Utescher, Hannes Grönner, Judith Sieker, und Sina Zarrieß. „WikiScenes with Descriptions: Aligning Paragraphs and Sentences with Images in Wikipedia Articles“. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), 93–105. Mexico City, Mexico: Association for Computational Linguistics, 2024. https://doi.org/10.18653/v1/2024.starsem-1.8.

  • Brinner, Marc, Sina Zarrieß, und Tina Heger. „Weakly Supervised Claim Localization in Scientific Abstracts“. In Robust Argumentation Machines, herausgegeben von Philipp Cimiano, Anette Frank, Michael Kohlhase, und Benno Stein, 14638:20–38. Cham: Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-63536-6_2.

  • Bunzeck, Bastian, und Sina Zarrieß. „Fifty shapes of BLiMP: syntactic learning curves in language models are not uniform, but sometimes unruly“. In Proceedings of the 2024 CLASP Conference on Multimodality and Interaction in Language Learning, herausgegeben von Amy Qiu, Bill Noble, David Pagmar, Vladislav Maraev, und Nikolai Ilinykh, 39–55. Gothenburg, Sweden: Association for Computational Linguistics, 2024. https://aclanthology.org/2024.clasp-1.7.

  • Hoeken, Sanne, Özge Alacam, Antske Fokkens, und Pia Sommerauer. „Methodological Insights in Detecting Subtle Semantic Shifts with Contextualized and Static Language Models“. In Findings of the Association for Computational Linguistics: EMNLP 2023, 3662–75. Singapore: Association for Computational Linguistics, 2023. https://doi.org/10.18653/v1/2023.findings-emnlp.237.

  • Junker, Simeon, und Sina Zarrieß. „Resilience through Scene Context in Visual Referring Expression Generation“. In Proceedings of the 17th International Natural Language Generation Conference, 344–57. Tokyo, Japan: Association for Computational Linguistics, 2024. https://aclanthology.org/2024.inlg-main.29/.

  • Lachenmaier, Clara, Eleonore Lumer, Hendrik Buschmeier, und Sina Zarrieß. „Towards Understanding the Entanglement of Human Stereotypes and System Biases in Human-Robot Interaction“. In Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, 646–49. Boulder CO USA: ACM, 2024. https://doi.org/10.1145/3610978.3640736.

  • Sieker, Judith, Simeon Junker, Ronja Utescher, Nazia Attari, Heiko Wersing, Hendrik Buschmeier, und Sina Zarrieß. „The Illusion of Competence: Evaluating the Effect of Explanations on Users’ Mental Models of Visual Question Answering Systems“. arXiv, 21. Oktober 2024. http://arxiv.org/abs/2406.19170.

Resources

  • Code and data on colour classification in Visual Genome: github
  • ManyNames: We were very happy to collaborate with the AMORE group for the collection of this dataset for object naming in real-world images github