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CaIRec: Calibrated Modality Imputation for Incomplete Multimodal Recommendation
Ruiyu Liu, Xiaohao Liu, Miaomiao Cai +2
Real-world multimodal recommender systems often face incomplete modality observations, where items lack images, text, or other content features. Such incompleteness weakens item re…
Dynamic Spectral Denoising with Global-Context Attention for Multi-Behavior Recommendation
Miaomiao Cai, Yunshan Ma, Fangqi Zhu +5
Multi-behavior recommendation improves target-behavior prediction by exploiting heterogeneous auxiliary feedback (e.g., view, collect, and cart), yet its robustness is undermined b…
Dual-Diffusional Generative Fashion Recommendation
Mingzhe Yu, Lei Wu, Qianru Sun +1
Personalized generative recommender systems have emerged as a promising solution for fashion recommendation. However, existing methods primarily rely on implicit visual embeddings…
Scattered Hypothesis Generation for Open-Ended Event Forecasting
He Chang, Zhulin Tao, Lifang Yang +2
Despite the importance of open-ended event forecasting for risk management, current LLM-based methods predominantly target only the most probable outcomes, neglecting the intrinsic…
Frozen LVLMs for Micro-Video Recommendation: A Systematic Study of Feature Extraction and Fusion
Huatuan Sun, Yunshan Ma, Changguang Wu +3
Frozen Large Video Language Models (LVLMs) are increasingly employed in micro-video recommendation due to their strong multimodal understanding. However, their integration lacks sy…
An item is worth one token in Multimodal Large Language Models-based Sequential Recommendation
Qiyong Zhong, Jiajie Su, Ming Yang +3
Sequential recommendations (SR) predict users' future interactions based on their historical behavior. The rise of Large Language Models (LLMs) has brought powerful generative and…
Pctx: Tokenizing Personalized Context for Generative Recommendation
Qiyong Zhong, Jiajie Su, Yunshan Ma +2
Generative recommendation (GR) models tokenize each action into a few discrete tokens (called semantic IDs) and autoregressively generate the next tokens as predictions, showing ad…