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A key improvement of the brand new ranking mechanism is to reflect a more correct preference pertinent to reputation, pricing coverage and slot impact primarily based on exponential decay model for on-line users. This paper studies how the net music distributor ought to set its ranking coverage to maximise the worth of on-line music ranking service. However, previous approaches typically ignore constraints between slot worth representation and related slot description representation in the latent house and lack sufficient mannequin robustness. Extensive experiments and analyses on the lightweight models show that our proposed methods obtain considerably increased scores and substantially enhance the robustness of each intent detection and slot filling. Unlike typical dialog fashions that depend on huge, complicated neural network architectures and enormous-scale pre-skilled Transformers to realize state-of-the-art results, our technique achieves comparable results to BERT and even outperforms its smaller variant DistilBERT on conversational slot extraction tasks. Still, even a slight enchancment may be value the price.
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