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• [5]
  

  2024 | Konferenzbeitrag | PUB-ID: 3001934

  Alaçam, Ö., Hoeken, S., & Zarrieß, S., 2024. Eyes Don`t Lie: Subjective Hate Annotation and Detection with Gaze. In Y. Al-Onaizan, M. Bansal, & Y. - N. Chen, eds. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Miami, Florida, USA: Association for Computational Linguistics, pp. 187-205.

  PUB | DOI | Download (ext.)
   
• [4]
  

  2024 | Report | Veröffentlicht | PUB-ID: 2992602

  Hammer, B., et al., 2024. Sustainable Life-Cycle of Intelligent Socio-Technical Systems,

  PUB | Dateien verfügbar | DOI
   
• [3]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2986803

  Hoeken, S., et al., 2023. Towards Detecting Lexical Change of Hate Speech in Historical Data. In N. Tahmasebi, ed. Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change. Stroudsburg, PA, USA: Association for Computational Linguistics, pp. 100-111.

  PUB | DOI
   
• [2]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2987176

  Hoeken, S., et al., 2023. Methodological Insights in Detecting Subtle Semantic Shifts with Contextualized and Static Language Models. In H. Bouamor, J. Pino, & K. Bali, eds. Findings of the Association for Computational Linguistics: EMNLP 2023. Stroudsburg, PA, USA: Association for Computational Linguistics, pp. 3662-3675.

  PUB | DOI
   
• [1]
  

  2023 | Konferenzbeitrag | PUB-ID: 2981214

  Hoeken, S., Zarrieß, S., & Alaçam, Ö., 2023. Identifying Slurs and Lexical Hate Speech via Light-Weight Dimension Projection in Embedding Space. In Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis. Toronto, Canada: Association for Computational Linguistics, pp. 278-289.

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