Creation-Recognition

ANCHOR: Agentic Noise Creation Framework for Human Simulation and Denoising Recommendation

arXiv:2606.05621v1 Announce Type: new Abstract: Distilling accurate user preferences from noisy implicit feedback remains a fundamental bottleneck in recommendation systems, highlighting the need for recommendation denoising. However, real-world data lack explicit noise annotations, forcing existing methods to rely on unsupervised side information or handcrafted heuristics. These approaches often incur high external costs, generalize poorly, or depend on unreliable priors, causing noise...