By arXiv.org -
2020-10-15
Humans learn language by listening, speaking, writing, reading, and also, via
interaction with the multimodal real world. Existing language pre-training
frameworks show the effectiveness of text-only ...
By arXiv.org -
2021-02-28
Modern natural language processing (NLP) methods employ self-supervised
pretraining objectives such as masked language modeling to boost the
performance of various application tasks. These pretraining ...
By arXiv.org -
2020-10-14
There is an increasing interest in studying natural language and computer
code together, as large corpora of programming texts become readily available
on the Internet. For example, StackOverflow curr ...
By arXiv.org -
2020-10-23
The recent "Text-to-Text Transfer Transformer" (T5) leveraged a unified
text-to-text format and scale to attain state-of-the-art results on a wide
variety of English-language NLP tasks. In this paper, ...
By arXiv.org -
2020-10-06
Literary tropes, from poetry to stories, are at the crux of human imagination
and communication. Figurative language such as a simile go beyond plain
expressions to give readers new insights and inspi ...
By arXiv.org -
2020-10-08
Multilingual pre-trained Transformers, such as mBERT (Devlin et al., 2019)
and XLM-RoBERTa (Conneau et al., 2020a), have been shown to enable the
effective cross-lingual zero-shot transfer. However, t ...