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Example-guided stylized response generation in zero-shot setting

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References

  1. Raina R, Battle A, Lee H, et al. Self-taught learning: transfer learning from unlabeled data. In: Proceedings of the 24th International Conference on Machine Learning, 2007. 759–766

  2. Sutskever I, Vinyals O, Le Q V. Sequence to sequence learning with neural networks. In: Proceedings of the 27th International Conference on Neural Information Processing Systems, 2014. 3104–3112

  3. Gao X, Zhang Y Z, Lee S, et al. Structuring latent spaces for stylized response generation. In: Proceedings of Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019. 1814–1823

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Acknowledgements

This work was supported by National Key Research and Development Program of China (Grant No. 2020AAA0106400), National Natural Science Foundation of China (Grant Nos. 61533018, U1936207, 61976211, 61702512), and Independent Research Project of National Laboratory of Pattern Recognition (Grant No. Z-2018013). This research work was also supported by Youth Innovation Promotion Association CAS.

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Authors and Affiliations

  1. National Laboratory of Pattern Recognition Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Guirong Bai, Shizhu He, Kang Liu & Jun Zhao

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Guirong Bai, Shizhu He, Kang Liu & Jun Zhao

Authors
  1. Guirong Bai
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  2. Shizhu He
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  3. Kang Liu
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  4. Jun Zhao
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Correspondence to Shizhu He.

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Bai, G., He, S., Liu, K. et al. Example-guided stylized response generation in zero-shot setting. Sci. China Inf. Sci. 65, 149103 (2022). https://doi.org/10.1007/s11432-020-3212-x

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  • DOI: https://doi.org/10.1007/s11432-020-3212-x

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