A naukri.com initiative
Arxiv
1w
164
Image Credit: Arxiv
Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment
- Cal-DPO is a new algorithm proposed for aligning large language models (LLMs) with human preference data.
- It addresses the limitation of the contrastive preference optimization by calibrating the implicit reward to ensure comparability with ground-truth rewards.
- Cal-DPO demonstrates theoretical advantages and significantly improves off-the-shelf methods in aligning LLMs with given preferences.
Read Full Article
9 Likes
For uninterrupted reading, download the app