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Beyond Keywords: Neural Retrieval with Context
Manage episode 444202215 series 3605861
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This research paper proposes two methods for improving the performance of neural retrieval models by incorporating contextual information. The first method involves a training procedure that clusters documents into batches based on similarity, creating more challenging training examples. The second method introduces a new architecture that augments the standard encoder with additional information about neighboring documents, allowing the model to dynamically learn corpus statistics. The paper demonstrates that both methods achieve better results than traditional biencoders, particularly in out-of-domain settings.
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