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Learning to match using local and distributed representations of text for web search
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https://doi.org/10.1145%2F3397271.3401075
While remarkably effective, the ranking models based on these LMs increase computational cost by orders of magnitude over prior approaches, particularly as they must feed each query-document pair through a massive neural network to compute a single relevance score