FairDiff: Mitigating the Self-Reinforcing Matthew Effect in Diffusion Recommender Models.

arXiv:2609.36671v2 Announce Type: replace Abstract: While the "Matthew Effect" and filter bubbles are widely recognized outcome-level biases in recommender systems, we reveal that Diffusion Recommender Models (DRMs) uniquely compound this issue through their g