20.500.12556/RUL-138840 Language models and task-driven learning for sarcasm detection Jezikovni modeli in učenje s prilagajanjem nalogi za prepoznavanje sarkazma In natural language processing, sarcasm detection determines whether a given text is sarcastic or not. It can have many real-world applications such as machine translation. In this work, we present three language modelling approaches and adapt them to the task of sarcasm detection. Two approaches are pretrained language models, BERT uses the encoder part of the transformer architecture and GPT-3 uses the decoder part of the transformer. The third method uses a newly-proposed task-driven learning technique TLM. We evaluated the methods using well-known metrics such as classification accuracy, precision and recall. GPT-3 performed the best in almost every aspect, with BERT being a close second. Our findings showed that TLM is very dependent on the task data and is therefore not suitable for a general task such as sarcasm detection. Zaznavanje sarkazma je postopek ugotavljanja, ali je besedilo sarkastično ali ne. Avtomatsko prepoznavanje sarkazma je pomemben vidik obdelave naravnega jezika in ima lahko veliko aplikacij, npr strojno prevajanje. V delu predstavljamo tri pristope jezikovnega modeliranja in jih prilagajamo nalogi odkrivanja sarkazma. Dva pristopa sta vnaprej naučena jezikovna modela, BERT uporablja kodirni del transformerske arhitekture, GPT-3 pa uporablja dekodirni del transformerja. Tretja metoda, TLM, uporablja novo predlagano tehniko učenja, ki temelji na ekstrakciji podatkov glede na dano nalogo. Metode smo ovrednotili z uporabo dobro znanih metrik, kot so klasifikacijska točnost, natančnost in priklic. Metoda GPT-3 se je izkazala za najboljšo v skoraj vseh vidikih, BERT pa je bil na drugem mestu. Naše ugotovitve so pokazale, da je TLM zelo odvisen od podatkov dane naloge in zato ni primeren za splošno nalogo, kot je odkrivanje sarkazma. natural language processing language models sarcasm detection transformer architecture obdelava naravnega jezika jezikovni modeli prepoznavanje sarkazma arhitektura transformer true false false Angleški jezik Slovenski jezik Diplomsko delo/naloga 2022-08-23 08:35:05 2022-08-23 08:35:11 2022-10-13 11:02:52 0000-00-00 00:00:00 2022 0 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 34862 125453827 Dimitrievikj_Aleksandar_-_Jezikovni_modeli_in_ucenje_s_prilagajanjem_nalogi_za_prepoznavanje_sar.pdf Dimitrievikj_Aleksandar_-_Jezikovni_modeli_in_ucenje_s_prilagajanjem_nalogi_za_prepoznavanje_sar.pdf 1 283B44935A745CF059FE4ACB18FB2B1D 7fdff802f81c6433424eb28c7123a6952c291f9da84fc637eba637f13d8ba712 bc5882d3-22ad-11ed-92af-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=159303 Fakulteta za računalništvo in informatiko 0 0 0