DAMDID 2024. Session 11. Information extraction from text I: Generative and Transformer-Based Models

SESSION 11. Information extraction from text I: Generative and Transformer-Based Models. Chair: Boris Dobrov 00:00 Exploring Fine-tuned Generative Models for Keyphrase Selection: A Case Study for Russian. Anna Glazkova and Dmitry Morozov 19:48 Questions 29:17  Applying Generative Neural Networks to Extract Argument Relations from Scientific Communication Texts. Alexey Sery, Daria Ilina, Elena Sidorova and Yury Zagorulko 50:06 Questions 59:38 Explaining Transformer-Based Models: a Comparative Study of flan-T5 and BERT Using Post-Hoc Methods. Alisher Rogov and Natalia Loukachevitch 01:12:41 Questions 01:16:50 An Experimental Study on Cross-domain Transformer-Based Term Recognition for Russian. Elena Bolshakova and Vladislav Semak 01:40:40 Questions