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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