Unsupervised Multimodal Reward Modeling.

arXiv:2610.12707v1 Announce Type: cross Abstract: Vision-language reward models are trained on annotated preference pairs, which are expensive to collect, can disagree, and are ranked by benchmark accuracy. We build one with no human preference label: a linear