A Unifying Lens on Supervised Fine-Tuning Through Target Distribution Design

Tong Xie, Yuanhao Ban, Yunqi Hong +3

Supervised fine-tuning (SFT) typically maximizes the likelihood of every token in a demonstrated trajectory. However, an observed token can be non-unique, noisy, or misaligned with…