From Noise to Order: Learning to Rank via Denoising Diffusion 事件

From Noise to Order: Learning to Rank via Denoising Diffusion arXiv:2602.11453v2 Announce Type: replace-cross Abstract: In information retrieval (IR), learning-to-rank (LTR) methods have traditionally limited themselves to discriminative machine learning approaches that model the probability of the document being relevant to the query given some feature representation of the query-document pair. In this work, we propose an alternative denoising diffusion-based deep generative approach to LTR th