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MinTL: Minimalist Transfer Learning for TaskOriented Dialogue Systems Zhaojiang Lin, Andrea Madotto, Genta Indra Winata, Pascale Fung Center for Artificial Intelligence Research (CAiRE) Department
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How to fill out zero-shot dialogue state tracking

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How to fill out zero-shot dialogue state tracking

01
First, identify the intended dialogue state and its corresponding values.
02
Next, prepare a set of possible utterances that a user may input to indicate the dialogue state.
03
Then, create a mapping between the possible utterances and the corresponding dialogue states.
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Finally, implement a model that can predict the dialogue state based on the user input using the mapping created.

Who needs zero-shot dialogue state tracking?

01
Developers working on chatbots or virtual assistants that need to accurately track the dialogue state without explicit training data.
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Companies looking to improve user experience by accurately predicting user intents in a conversational setting.
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Zero-shot dialogue state tracking is a method used in natural language processing where a system can manage dialogue states without prior training on specific task-oriented dialogues. It utilizes general language understanding to infer user intents and track the state of the conversation.
To fill out zero-shot dialogue state tracking, one must ensure that the system can recognize and understand user intents without fine-tuning on domain-specific data. This involves providing sufficient context, examples, or prompts to guide the model in making accurate inferences.
The purpose of zero-shot dialogue state tracking is to enable dialogue systems to comprehend and manage conversations seamlessly in new contexts or domains without necessitating retraining, thereby increasing adaptability and efficiency.
The information that must be reported includes user intents, dialogue turns, contextual information, and the resultant state of the dialogue as inferred by the tracking model.
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