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Found 3 papers, 1 papers with code
Addressing Slot-Value Changes in Task-oriented Dialogue Systems through Dialogue Domain Adaptation
Recent task-oriented dialogue systems learn a model from annotated dialogues, and such dialogues are in turn collected and annotated so that they are consistent with certain domain knowledge.
When to Retrieve: Teaching LLMs to Utilize Information Retrieval Effectively
Through our analysis, we demonstrate that Adapt-LLM is able to generate the <RET> token when it determines that it does not know how to answer a question, indicating the need for IR, while it achieves notably high accuracy levels when it chooses to rely only on its parametric memory.
Unraveling ChatGPT: A Critical Analysis of AI-Generated Goal-Oriented Dialogues and Annotations
Large pre-trained language models have exhibited unprecedented capabilities in producing high-quality text via prompting techniques.
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