Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation

The latency of neural ranking models at query time is largely dependent on the architecture and deliberate choices by their designers to trade-off effectiveness for higher efficiency. This focus on low query latency of a rising number of efficient ranking architectures make them feasible for production deployment... (read more)

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