Think Twice Before You Answer: Mitigating Biases of Question Answering Models – Mgr. Lukáš Mikula
Mgr. Lukáš Mikula
Master's thesis
Think Twice Before You Answer: Mitigating Biases of Question Answering Models
Think Twice Before You Answer: Mitigating Biases of Question Answering Models
Abstract:
Veľké jazykové modely (z angl. Large Language Models) založené na architektúre Transformerov predstavujú najlepšie modely pre vačšinu problémov spracovania prirodzeného jazyka (z angl. Natural Language Modeling). Napriek tomu majú tieto modely tendenciu učiť sa skreslenia a systematické chyby z trénovacích datasetov. Toto učenie im síce môže pomôcť na datasetoch s rovnakou distribúciou, lenže znižuje …moreAbstract:
Large Language Models based on Transformer architecture hold state-of-the-art in a majority of Natural Language Modeling tasks. Nevertheless, these models tend to learn biases from training dataset, which help them on the training dataset, but hurt their out-of-domain accuracy as a result. This work focuses on obtaining more robust BERT models for the Extractive Question Answering task. We explore …more
Language used: English
Date on which the thesis was submitted / produced: 17. 5. 2022
Identifier:
https://is.muni.cz/th/adh58/
Thesis defence
- Date of defence: 22. 6. 2022
- Supervisor: Mgr. Michal Štefánik
- Reader: RNDr. Vít Suchomel, Ph.D.
Citation record
Full text of thesis
Contents of on-line thesis archive
Published in Theses:- světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatikyMasaryk University
Faculty of InformaticsMaster programme / field:
Artificial intelligence and data processing / Big data
Theses on a related topic
-
Cross-lingual sentiment analysis with BERT
Mohsen Amini Riseh -
BERT models in document classification
Ahmad Arsalan Khateeb -
Analýza díla Jiřiny Prekopové a Berta Hellingera z transkulturní perspektivy
Lukáš Nosek