A Survey for LLM Tuning Methods:Classifying Approaches Based on Model Internal Accessibility
Kyotaro Nakajima, Hwichan Kim, Tosho Hirasawa, Taisei Enomoto, Zhousi Chen, Mamoru Komachi
- Anthology ID:
- 2024.paclic-1.52
- Volume:
- Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation
- Month:
- December
- Year:
- 2024
- Address:
- Tokyo, Japan
- Editors:
- Nathaniel Oco, Shirley N. Dita, Ariane Macalinga Borlongan, Jong-Bok Kim
- Venue:
- PACLIC
- SIG:
- Publisher:
- Tokyo University of Foreign Studies
- Note:
- Pages:
- 542–555
- Language:
- URL:
- https://preview.aclanthology.org/fix-sig-urls/2024.paclic-1.52/
- DOI:
- Cite (ACL):
- Kyotaro Nakajima, Hwichan Kim, Tosho Hirasawa, Taisei Enomoto, Zhousi Chen, and Mamoru Komachi. 2024. A Survey for LLM Tuning Methods:Classifying Approaches Based on Model Internal Accessibility. In Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation, pages 542–555, Tokyo, Japan. Tokyo University of Foreign Studies.
- Cite (Informal):
- A Survey for LLM Tuning Methods:Classifying Approaches Based on Model Internal Accessibility (Nakajima et al., PACLIC 2024)
- PDF:
- https://preview.aclanthology.org/fix-sig-urls/2024.paclic-1.52.pdf