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A key enchancment of the brand new rating mechanism is to mirror a more accurate desire pertinent to popularity, pricing policy and slot impact based mostly on exponential decay mannequin for on-line users. This paper research how the online music distributor should set its rating policy to maximize the worth of on-line music rating service. However, previous approaches usually ignore constraints between slot value illustration and related slot description representation in the latent house and lack enough mannequin robustness. Extensive experiments and analyses on the lightweight fashions present that our proposed strategies obtain significantly increased scores and substantially enhance the robustness of both intent detection and slot filling. Unlike typical dialog models that rely on large, complicated neural network architectures and huge-scale pre-trained Transformers to realize state-of-the-artwork outcomes, our method achieves comparable outcomes to BERT and even outperforms its smaller variant DistilBERT on conversational slot extraction duties. Still, even a slight enchancment may be value the cost.
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