Training Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model
Kosuke Takahashi, Takahiro Omi, Kosuke Arima, Tatsuya Ishigaki
- 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:
- 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)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2023.paclic-1.78.pdf