Senaste titlar

  • Proceedings of the 2023 CLASP Conference on Learning with Small Data 

    Breitholtz, Ellen; Lappin, Shalom; Loáiciga, Sharid; Ilinykh, Nikolai; Dobnik, Simon; Centre for Linguistic Theory and Studies in Probability (CLASP); Department of Philosophy, Linguistics and Theory of Science (FLoV); University of Gothenburg (The Association for Computational Linguistics, 2023-09-10)
    The purpose of our conference is to bring together researchers from several areas of NLP, addressing datasets, methods and limits of effective (machine) learning with small data containing natural language and associated ...
  • Proceedings of the 2022 CLASP Conference on (Dis)embodiment 

    Dobnik, Simon; Grove, Julian; Sayeed, Asad; Department of Philosophy, Linguistics and Theory of Science (FLoV); Centre for Linguistic Theory and Studies in Probability (CLASP) (The Association for Computational Linguistics, 2022-09-14)
    Dis)embodiment brings together researchers from several areas examining the role of grounding and embodiment in modelling human language and behaviour – or limits thereof. The conference covers areas such as machine learning, ...
  • CLASP Papers in Computational Linguistics 

    Howes, Christine; Dobnik, Simon; Ellen, Breitholtz; Department of Philosophy, Linguistics and Theory of Science (FLOV); University of Gothenburg (Centre for Linguistic Theory and Studies in Probability (CLASP), 2020-02-25)
    This volume showcases research which aims to bridge the gaps between research on dialogue and research on perception. Dialogue research investigates how natural language is used in interaction between interlocutors and ...
  • CLASP Papers in Computational Linguistics 

    Simon, Dobnik; Shalom, Lappin; Department of Philosophy, Linguistics and Theory of Science (FLOV); University of Gothenburg (Centre for Linguistic Theory and Studies in Probability (CLASP), 2017-11)
    The past two decades have seen impressive progress in a variety of areas of AI, particularly NLP, through the application of machine learning methods to a wide range of tasks. With the intensive use of deep learning methods ...