Scaling Articulated Rationales for MLLM-based Recommendation

arXiv:2609.17639v1 Announce Type: cross Abstract: Modern recommendation systems largely infer user preferences from implicit behaviors such as clicks, watch time, and negative feedback, but these signals reveal what users do rather than why they like or dislik