Training Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model

Kosuke Takahashi; Takahiro Omi; Kosuke Arima; Tatsuya Ishigaki

Training Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model

Kosuke Takahashi, Takahiro Omi, Kosuke Arima, Tatsuya Ishigaki

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Anthology ID:: 2023.paclic-1.78
Volume:: Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation
Month:: December
Year:: 2023
Address:: Hong Kong, China
Editors:: Chu-Ren Huang, Yasunari Harada, Jong-Bok Kim, Si Chen, Yu-Yin Hsu, Emmanuele Chersoni, Pranav A, Winnie Huiheng Zeng, Bo Peng, Yuxi Li, Junlin Li
Venue:: PACLIC
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 786–791
Language:
URL:: https://aclanthology.org/2023.paclic-1.78/
DOI:
Bibkey:
Cite (ACL):: Kosuke Takahashi, Takahiro Omi, Kosuke Arima, and Tatsuya Ishigaki. 2023. Training Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model. In Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation, pages 786–791, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):: Training Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model (Takahashi et al., PACLIC 2023)
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PDF:: https://aclanthology.org/2023.paclic-1.78.pdf

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@inproceedings{takahashi-etal-2023-training,
    title = "Training Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model",
    author = "Takahashi, Kosuke  and
      Omi, Takahiro  and
      Arima, Kosuke  and
      Ishigaki, Tatsuya",
    editor = "Huang, Chu-Ren  and
      Harada, Yasunari  and
      Kim, Jong-Bok  and
      Chen, Si  and
      Hsu, Yu-Yin  and
      Chersoni, Emmanuele  and
      A, Pranav  and
      Zeng, Winnie Huiheng  and
      Peng, Bo  and
      Li, Yuxi  and
      Li, Junlin",
    booktitle = "Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation",
    month = dec,
    year = "2023",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.paclic-1.78/",
    pages = "786--791"
}

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%0 Conference Proceedings
%T Training Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model
%A Takahashi, Kosuke
%A Omi, Takahiro
%A Arima, Kosuke
%A Ishigaki, Tatsuya
%Y Huang, Chu-Ren
%Y Harada, Yasunari
%Y Kim, Jong-Bok
%Y Chen, Si
%Y Hsu, Yu-Yin
%Y Chersoni, Emmanuele
%Y A, Pranav
%Y Zeng, Winnie Huiheng
%Y Peng, Bo
%Y Li, Yuxi
%Y Li, Junlin
%S Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation
%D 2023
%8 December
%I Association for Computational Linguistics
%C Hong Kong, China
%F takahashi-etal-2023-training
%U https://aclanthology.org/2023.paclic-1.78/
%P 786-791

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Markdown (Informal)

[Training Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model](https://aclanthology.org/2023.paclic-1.78/) (Takahashi et al., PACLIC 2023)

Training Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model (Takahashi et al., PACLIC 2023)

ACL

Kosuke Takahashi, Takahiro Omi, Kosuke Arima, and Tatsuya Ishigaki. 2023. Training Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model. In Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation, pages 786–791, Hong Kong, China. Association for Computational Linguistics.