Data Advisor: Dynamic Data Curation for Safety Alignment of Large Language Models
Fei Wang, Ninareh Mehrabi, Palash Goyal, Rahul Gupta, Kai-Wei Chang, Aram Galstyan
Abstract
Data are crucial element in large language model (LLM) alignment. Recent studies have explored using LLMs for efficient data collection. However, LLM-generated data often suffers from quality issues, with underrepresented or absent aspects and low-quality datapoints. To address these problems, we propose Data Advisor, an enhanced LLM-based method for generating data that takes into account the characteristics of the desired dataset. Starting from a set of pre-defined principles in hand, Data Advisor monitors the status of the generated data, identifies weaknesses in the current dataset, and advises the next iteration of data generation accordingly. Data Advisor can be easily integrated into existing data generation methods to enhance data quality and coverage. Experiments on safety alignment of three representative LLMs (i.e., Mistral, Llama2, and Falcon) demonstrate the effectiveness of Data Advisor in enhancing model safety against various fine-grained safety issues without sacrificing model utility.- Anthology ID:
- 2024.emnlp-main.461
- 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:
- 8089–8100
- Language:
- URL:
- https://aclanthology.org/2024.emnlp-main.461
- DOI:
- 10.18653/v1/2024.emnlp-main.461
- Cite (ACL):
- Fei Wang, Ninareh Mehrabi, Palash Goyal, Rahul Gupta, Kai-Wei Chang, and Aram Galstyan. 2024. Data Advisor: Dynamic Data Curation for Safety Alignment of Large Language Models. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 8089–8100, Miami, Florida, USA. Association for Computational Linguistics.
- Cite (Informal):
- Data Advisor: Dynamic Data Curation for Safety Alignment of Large Language Models (Wang et al., EMNLP 2024)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2024.emnlp-main.461.pdf