Zitong Huang

Token-Level Off-Policy Learning for Faithful Generation Under Distribution Shift

Zitong Huang, Gustavo Lucas Carvalho, Deqing Fu, Robin Jia

We propose Token-Level Off-Policy Labeling (TOPL), an off-policy training paradigm that reframes post-training as a token-level correctness prediction task. Our key intuition is that by training the model to distinguish good and bad tokens in a response, we naturally guide the mo…Read more