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  license: apache-2.0
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  license: apache-2.0
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+ # FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for Task-Oriented Dialogue
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+ We present our dialogue-pertaining model, FutureTOD, which distills future knowledge into the representation of the previous dialogue context using a self-training framework. Extensive experiments on diverse downstream dialogue tasks demonstrate the effectiveness of our model, especially its generalization, robustness, and ability to learn discriminative dialogue representations.
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+ [This paper](https://arxiv.org/abs/2306.10315) has been accepted at the ACL 2023 Main Conference.
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+ ## Usage
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+ We release our futuretod-base-v1.0 model here. You can use this model for downstream TOD tasks follow instructions in [FutureTOD](https://github.com/Zeng-WH/FutureTOD).
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+ ## Quotation
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+ If you find our work helpful, please consider quoting the following papers.
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+ ```
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+ @article{zeng2023futuretod,
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+ title={FutureTOD: Teaching Future Knowledge to Pre-trained Language Model for Task-Oriented Dialogue},
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+ author={Zeng, Weihao and He, Keqing and Wang, Yejie and Zeng, Chen and Wang, Jingang and Xian, Yunsen and Xu, Weiran},
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+ journal={arXiv preprint arXiv:2306.10315},
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+ year={2023}
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+ }
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+ ```