Before revision: Pre-trained language models such as BERT have recently contributed to significant advances in Natural Language Processing tasks. Interestingly, while multilingual BERT models have demonstrated impressive results, recent works have shown how monolingual BERT can also be competitive in zero-shot cross-lingual settings. This suggests that the abstractions learned by these models can transfer across languages, even when trained on monolingual data .
After revision: Pre-trained language models such as BERT have recently contributed to significant advances in NLP tasks. Recently, multi-modal versions of BERT have been developed, using heavy pre-training relying on vast corpora of aligned textual and image data, primarily applied to classification tasks such as VQA .