@inproceedings{
wang2023reward,
title={Reward Model Aggregation},
author={Zihao Wang and Chirag Nagpal and Alexander D'Amour and Victor Veitch and Sanmi Koyejo},
booktitle={NeurIPS 2023 Workshop on Instruction Tuning and Instruction Following},
year={2023},
url={https://openreview.net/forum?id=KGBNAJCuPf}
}
Aligning language models requires guiding outputs towards desired properties using reward models. This paper tackles the challenge of combining multiple reward models for diverse objectives. We introduce methods for aggregating these rewards using logical operations. Experiments confirm our methods beat traditional aggregation techniques and underscore the significance of proper reference values.
Reward Model Aggregation
Zihao Wang Chirag Nagpal Alexander D'Amour Victor Veitch Sanmi Koyejo