Papers with large-scale task-oriented dialogue data

1 papers
OPAL: Ontology-Aware Pretrained Language Model for End-to-End Task-Oriented Dialogue (2023.tacl-1)

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Challenge: Existing task-oriented dialogue systems lack ontology-aware pretraining methods for task-orientated dialogue.
Approach: They propose an ontology-aware pretrained language model (OPAL) for end-to-end task-oriented dialogue (TOD) . they propose to pretrain on large-scale contextual text data to bridge the gap between the pretraining method and downstream tasks.
Outcome: The proposed model achieves an exciting boost and obtains competitive performance even without any TOD data on CamRest676 and MultiWOZ benchmarks.

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