Unveiling the Hidden Linearity in Transformer Decoders: New Insights for Efficient Pruning and Enhanced Performance

Transformers have greatly transformed natural language processing, delivering remarkable progress across various applications. Nonetheless, despite their widespread use and accomplishments, ongoing research continues to delve into the intricate workings of these models, with a particular focus on the linear nature of intermediate embedding transformations. This less explored aspect poses significant implications for further advancements in […]

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