Preprint
Oct 2026
Generate What You Can Trust: Content Credibility in Generative Recommenders
Generative recommendation (GR) represents items with semantic IDs (i.e., discrete token sequences) and generates target item tokens as recommendations. Despite its promising results, existing methods predominantly optimize for accuracy while neglecting the credibility of the recommendations they generate. This oversigh...
Zhuo Cai, Guang-Hao Wu, Shou-Jin Wang et al.
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