Papers with End-to-end Task-Oriented Dialog

1 papers
Synergizing In-context Learning with Hints for End-to-end Task-oriented Dialog Systems (2024.emnlp-main)

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Challenge: Existing end-to-end task-oriented dialogue systems require extensive training datasets to perform well.
Approach: They propose a system that synergizes LLMs with task-specific hints to improve alignment in low-data settings.
Outcome: The proposed model improves alignment in low-data settings while retaining competitive performance in full-data environments.

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