Scaling Articulated Rationales for MLLM-based Recommendation.

arXiv:2609.17639v2 Announce Type: replace-cross Abstract: We presented SARA, an industrial framework that transforms sparse articulated user rationales into scalable recommendation signals. Its data engine curates questionnaire responses into SARA-HQ, providin