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• [4]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2985222

  Sieker, J., and Zarrieß, S. (2023). “When Your Language Model Cannot Even Do Determiners Right: Probing for Anti-Presuppositions and the Maximize Presupposition! Principle” in Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP, Belinkov, Y., Hao, S., Jumelet, J., Kim, N., McCarthy, A., Mohebbi, H., and Association for Computational Linguistics eds. 180–198.

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• [3]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2983376

  Sieker, J., Bott, O., Solstad, T., and Zarrieß, S. (2023). “Beyond the Bias: Unveiling the Quality of Implicit Causality Prompt Continuations in Language Models” in Proceedings of the 16th International Natural Language Generation Conference, Keet , C. M., Lee, H. - Y., Zarrieß, S., and Association for Computational Linguistics eds. 206–220.

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• [2]
  

  2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968165

  Sieker, J., and Solstad, T. (2022). “Projective variability of (semi)factive verbs in family of sentence contexts: A rating study” in Proceedings of the 23rd Amsterdam Colloquium , Degano, M., Roberts, T., Sbardolini, G., Schouwstra, M., and Institute for Logic, Language and Computation (ILLC) eds. (Amsterdam), 282-289.

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• [1]
  

  2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2965490

  Reiter, N., Sieker, J., Guhr, S., Gius, E., and Zarrieß, S. (2022). “Exploring Text Recombination for Automatic Narrative Level Detection” in Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022) (European Language Resources Association (ELRA), 3346-3353.

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