Reranking Overgenerated Responses for End-to-End Task-Oriented Dialogue Systems (2024.lrec-main)
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| Challenge: | End-to-end task-oriented dialogue systems fall into the so-called ‘likelihood trap’, resulting in generated responses which are dull, repetitive, and inconsistent with dialogue history. |
| Approach: | They propose a reranking method to select high-quality items from the initial overgenerated list without the availability of the gold response. |
| Outcome: | The proposed method is based on a multi-woz dataset and human evaluation. |
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