Echoes in Filter Bubble: Diagnosing and Curing Popularity Bias in Generative Recommenders

In three linesStudy on popularity bias in Generative Recommenders (GRs). Authors identify bias stems from token-level optimization flaw and undifferentiated item tokenization. They propose Ghost, a GR with asymmetric unlikelihood optimization and skeleton-founded tokenization, validated across 3 datasets.

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