PUB - Publikationen an der Universität Bielefeld

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• [7]
  

  2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2969752

  Schüz, S., Gatt, A., & Zarrieß, S. (2023). Rethinking symbolic and visual context in Referring Expression Generation. Frontiers in Artificial Intelligence, 6, 18. https://doi.org/10.3389/frai.2023.1067125

  PUB | PDF | DOI | WoS | PubMed | Europe PMC
   
• [6]
  

  2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2967316

  Alaçam, Ö., Schüz, S., Wegrzyn, M., Kißler, J., & Zarrieß, S. (2022). Exploring Semantic Spaces for Detecting Clustering and Switching in Verbal Fluency. Proceedings of the 29th International Conference on Computational Linguistics, Coling, 29(2022), 178-191. International Committee on Computational Linguistics.

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• [5]
  

  2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2957091

  Zarrieß, S., Voigt, H., & Schüz, S. (2021). Decoding Methods in Neural Language Generation: A Survey. Information, 12(9), 355. https://doi.org/10.3390/info12090355

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• [4]
  

  2021 | Konferenzbeitrag | PUB-ID: 2958059

  Schüz, S., & Zarrieß, S. (2021). Decoupling Pragmatics: Discriminative Decoding for Referring Expression Generation. Proceedings of the Reasoning and Interaction Conference (ReInAct 2021), 47-52. Gothenburg, Sweden: Association for Computational Linguistics.

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• [3]
  

  2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2956772

  Zarrieß, S., Buschmeier, H., Han, T., & Schüz, S. (2021). Decoding, fast and slow: A case study on balancing trade-offs in incremental, character-level pragmatic reasoning. Proceedings of the 14th International Conference on Natural Language Generation, 371–376.

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• [2]
  

  2021 | Konferenzbeitrag | PUB-ID: 2955817

  Schüz, S., Han, T., & Zarrieß, S. (2021). Diversity as a By-Product: Goal-oriented Language Generation Leads to Linguistic Variation. Proceedings of the 22nd Annual SIGdial Meeting on Discourse and Dialogue, Forthcoming. Association for Computational Linguistics.

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• [1]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2955804

  Schüz, S., & Zarrieß, S. (2020). Knowledge Supports Visual Language Grounding: A Case Study on Colour Terms. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 6536-6542. Stroudsburg, PA, USA: Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.acl-main.584

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