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Found 2 papers, 2 papers with code
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data
Deep neural networks (DNNs) used for brain-computer-interface (BCI) classification are commonly expected to learn general features when trained across a variety of contexts, such that these features could be fine-tuned to specific contexts.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
On Losses for Modern Language Models
BERT set many state-of-the-art results over varied NLU benchmarks by pre-training over two tasks: masked language modelling (MLM) and next sentence prediction (NSP), the latter of which has been highly criticized.
