Two methods using multiple unsupervised rankers for soft labels and filtering harmful examples allow learning-to-rank to beat BM25 with far fewer training examples.
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Learning More From Less: Towards Strengthening Weak Supervision for Ad-Hoc Retrieval
Two methods using multiple unsupervised rankers for soft labels and filtering harmful examples allow learning-to-rank to beat BM25 with far fewer training examples.