Oral presentation of the conf paper: [Parameter-Efficient Low-Resource Dialogue State Tracking by Prompt Tuning](PromptDST). In the collaboration work with [Amazon Alexa AI](https://www.amazon.science/research-areas/conversational-ai-natural-language-processing), we introduce [a dialogue state tracking model](pubs/ma-etal-2023-parameter) tuning less than 1% of LM parameters and achieves better low-resource performance with prompt tuning techniques.
Aug 1, 2023
New INTERSPEECH paper! In the collaboration work with [Amazon Alexa AI](https://www.amazon.science/research-areas/conversational-ai-natural-language-processing), we introduce [a dialogue state tracking model](../publication/ma-etal-2023-parameter) tuning less than 1% of LM parameters and achieves better low-resource performance with prompt tuning techniques.
May 1, 2023