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This paper studies how the net music distributor should set its rating coverage to maximise the worth of on-line music ranking service. However, earlier approaches typically ignore constraints between slot value illustration and related slot description representation within the latent area and lack sufficient model robustness.
Extensive experiments and analyses on the lightweight models present that our proposed strategies achieve significantly greater scores and substantially enhance the robustness of each intent detection and slot filling. Unlike typical dialog fashions that rely on large, complex neural network architectures and large-scale pre-educated Transformers to attain state-of-the-art results, our technique achieves comparable outcomes to BERT and even outperforms its smaller variant DistilBERT on conversational slot extraction duties.
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