Scaling Articulated Rationales for MLLM-based Recommendation
These findings establish articulated rationales as a useful complement to behavioral and content signals, and demonstrate a practical role for MLLMs in scaling sparse human explanations into preference information that improves industrial recommendation.
Hao-Ke Xiao, Yue-Yang Liu, Yu-Hui Zhang et al.
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