DeMPT: Decoding-enhanced Multi-phase Prompt Tuning for Making LLMs Be Better Context-aware Translators
Xinglin Lyu, Junhui Li, Yanqing Zhao, Min Zhang, Daimeng Wei, Shimin Tao, Hao Yang, Min Zhang
- Anthology ID:
- 2024.emnlp-main.1131
- Volume:
- Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
- Month:
- November
- Year:
- 2024
- Address:
- Miami, Florida, USA
- Editors:
- Yaser Al-Onaizan, Mohit Bansal, Yun-Nung Chen
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 20280–20295
- Language:
- URL:
- https://preview.aclanthology.org/jlcl-multiple-ingestion/2024.emnlp-main.1131/
- DOI:
- 10.18653/v1/2024.emnlp-main.1131
- Cite (ACL):
- Xinglin Lyu, Junhui Li, Yanqing Zhao, Min Zhang, Daimeng Wei, Shimin Tao, Hao Yang, and Min Zhang. 2024. DeMPT: Decoding-enhanced Multi-phase Prompt Tuning for Making LLMs Be Better Context-aware Translators. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 20280–20295, Miami, Florida, USA. Association for Computational Linguistics.
- Cite (Informal):
- DeMPT: Decoding-enhanced Multi-phase Prompt Tuning for Making LLMs Be Better Context-aware Translators (Lyu et al., EMNLP 2024)
- PDF:
- https://preview.aclanthology.org/jlcl-multiple-ingestion/2024.emnlp-main.1131.pdf