DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering

Transformer-based QA models use input-wide self-attention -- i.e. across both the question and the input passage -- at all layers, causing them to be slow and memory-intensive. It turns out that we can get by without input-wide self-attention at all layers, especially in the lower layers... (read more)

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