Papers by Samuel Stern
MetaASSIST: Robust Dialogue State Tracking with Meta Learning (2022.emnlp-main)
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| Challenge: | Existing dialogue datasets contain lots of noise in their state annotations. |
| Approach: | They propose a framework to train robust dialogue state tracking models by combining pseudo and vanilla labels by a common weighting parameter. |
| Outcome: | The proposed framework achieves state-of-the-art accuracy of 80.10% on multiWOZ 2.4. |