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Training with Missed Targets in Generative Recommendation: Separating Supervision from Probability Competition
Generative recommenders return a limited candidate set and may omit observed targets before reranking. A training strategy appends these missed targets to reranker training lists, although inference still ranks only original candidates. This operation simultaneously changes retrieved-target weight,
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