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Despite the effectiveness of utilizing the BERT model for document ranking,the high computational cost of such approaches limits their uses. To this end,this paper first empirically investigates the effectiveness of two knowledgedistillation models on the document ranking task. In addition, on top of therecently proposed TinyBERT model, two simplifications are proposed. Evaluationson two different and widely-used benchmarks demonstrate that SimplifiedTinyBERT with the proposed simplifications not only boosts TinyBERT, but alsosignificantly outperforms BERT-Base when providing 15$\times$ speedup.

Simplified TinyBERT: Knowledge Distillation for Document Retrieval