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Found 3 papers, 1 papers with code
More Room for Language: Investigating the Effect of Retrieval on Language Models
Retrieval-augmented language models pose a promising alternative to standard language modeling.
Not all layers are equally as important: Every Layer Counts BERT
This paper introduces a novel modification of the transformer architecture, tailored for the data-efficient pretraining of language models.
Ranked #6 on
Linguistic Acceptability
on CoLA
BRENT: Bidirectional Retrieval Enhanced Norwegian Transformer
After training, we also separate the language model, which we call the reader, from the retriever components, and show that this can be fine-tuned on a range of downstream tasks.
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