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Pit One Against Many: Leveraging Attention-head Embeddings for Parameter-efficient Multi-head Attention
Scaling pre-trained language models has resulted in large performance gains in various natural language processing tasks but comes with a large cost in memory requirements.
HashFormers: Towards Vocabulary-independent Pre-trained Transformers
These embeddings are subsequently fed into transformer layers for text classification.
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