To encode the text input, we use BERT (Devlin et al., 2019), a transformer-based language model (Vaswani et al., 2017) that achieves state-ofthe-art performance on various NLP tasks.
we first fine-tune the BERT-base model using the masked language model and next sentence pre-diction objectives on the subtitles and QA pairs from TVQA+ train set.