Parameter-Efficient Low-Resource Dialogue State Tracking by Prompt Tuning
We use soft prompt tokens to learn task properties, incorporate segment information and reiterate the task before predicting value. Our method drastically reduces the number of parameters needed to less than 0.5% of prior works while achieving better low-resource dialogue state tracking performance.
Jan 20, 2023
Implicit Discourse Relation Identification for Open-domain Dialogues
A novel dataset of implicit discourse relation argument pairs and labels for dialogic turns and a novel discourse relation identification pipeline specifically tuned for open-domain dialogue systems
Jul 28, 2019