Zero-Shot Transfer Learning with Synthesized Data for Multi-Domain Dialogue State Tracking

Author:

Campagna Giovanni,Foryciarz Agata,Moradshahi Mehrad,Lam Monica

Publisher

Association for Computational Linguistics

Cited by 15 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Deep Learning for Natural Language Processing;Deep Learning and Reinforcement Learning;2023-11-15

2. Exploring Usability Issues in Instruction-Based and Schema-Based Authoring of Task-Oriented Dialogue Agents;Proceedings of the 5th International Conference on Conversational User Interfaces;2023-07-19

3. Choice Fusion As Knowledge For Zero-Shot Dialogue State Tracking;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

4. Zero-shot transfer learned generic AI models for prediction of optimally ripe climacteric fruits;Scientific Reports;2023-05-05

5. A Dual Prompt Learning Framework for Few-Shot Dialogue State Tracking;Proceedings of the ACM Web Conference 2023;2023-04-30

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