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• [4]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2985222

  Sieker J, Zarrieß S. When Your Language Model Cannot Even Do Determiners Right: Probing for Anti-Presuppositions and the Maximize Presupposition! Principle. In: Belinkov Y, Hao S, Jumelet J, et al., eds. Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP. 2023: 180–198.

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• [3]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2983376

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

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• [2]
  

  2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968165

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

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• [1]
  

  2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2965490

  Reiter N, Sieker J, Guhr S, Gius E, Zarrieß S. 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); 2022: 3346-3353.

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