Vier wissenschaftliche Beiträge unserer Fachrichtung wurden bei NoDaLiDa und LLMs for HPSS angenommen. Herzlichen Glückwunsch an alle Autorinnen und Autoren!
- “Predictability of Microsyntactic Units across Slavic Languages: A translation-based Study” von Maria Kunilovskaya, Iuliia Zaitova, Wei Xue, Irina Stenger and Tania Avgustinova (NoDaLiDa, Paper).
- “Diachronic Analysis of Phrasal Verbs in English Scientific Writing” von Diego Alves (NoDaLiDa, Paper).
- “Towards Interpretable Models: Bridging Traditional and Deep Learning Methods for Tracing Linguistic Change in English Scientific Writing” von Sofia Aguilar and Stefania Degaetano-Ortlieb (LLMs for HPSS, Abstract).
- “Leveraging Large Language Models for Metadata Enrichment and Diachronic Analysis of Chemical Knowledge in Historical Scientific Texts” von Diego Alves, Sergei Bagdasarov and Badr M. Abdullah (LLMs for HPSS, Abstract).