3 papers
cs.IR2026
MCLMR: A Model-Agnostic Causal Learning Framework for Multi-Behavior Recommendation
Ranxu Zhang, Junjie Meng, Ying Sun +5
Multi-Behavior Recommendation (MBR) leverages multiple user interaction types (e.g., views, clicks, purchases) to enrich preference modeling and alleviate data sparsity issues in t…
cs.LG2026
Latent Shadows: The Gaussian-Discrete Duality in Masked Diffusion
Guinan Chen, Xunpeng Huang, Ying Sun +3
Masked discrete diffusion is a dominant paradigm for high-quality language modeling where tokens are iteratively corrupted to a mask state, yet its inference efficiency is bottlene…
cs.IR2026
Enhancing LLM-based Recommendation with Preference Hint Discovery from Knowledge Graph
Yuting Zhang, Ziliang Pei, Chao Wang +2
LLMs have garnered substantial attention in recommendation systems. Yet they fall short of traditional recommenders when capturing complex preference patterns. Recent works have tr…