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20242026
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cs.IR2026

SynGR: Unleashing the Potential of Cross-Modal Synergy for Generative Recommendation

Wei Chen, Xingyu Guo, Shuang Li +6

Generative Recommendation (GR) has emerged as a promising paradigm by formulating item recommendation as a sequence-to-sequence generation task over item identifiers. Recent studie…

cs.IR2026

LASAR: Latent Adaptive Semantic Aligned Reasoning for Generative Recommendation

Yiwen Chen, Fuwei Zhang, Zehao Chen +8

Large Language Models (LLMs) have demonstrated powerful reasoning capabilities through Chain-of-Thought (CoT) in various tasks, yet the inefficiency of token-by-token generation hi…

cs.IR2026

TextBridgeGNN: Pre-training Graph Neural Network for Cross-Domain Recommendation via Text-Guided Transfer

Yiwen Chen, Yiqing Wu, Huishi Luo +3

Graph-based recommendation has achieved great success in recent years. The classical graph recommendation model utilizes ID embedding to store essential collaborative information.…

cs.IR2025

FLeW: Facet-Level and Adaptive Weighted Representation Learning of Scientific Documents

Zheng Dou, Deqing Wang, Fuzhen Zhuang +2

Scientific document representation learning provides powerful embeddings for various tasks, while current methods face challenges across three approaches. 1) Contrastive training w…

cs.IR2025

ORCA: Mitigating Over-Reliance for Multi-Task Dwell Time Prediction with Causal Decoupling

Huishi Luo, Fuzhen Zhuang, Yongchun Zhu +6

Dwell time (DT) is a critical post-click metric for evaluating user preference in recommender systems, complementing the traditional click-through rate (CTR). Although multi-task l…

cs.IR2025

CDC: Causal Domain Clustering for Multi-Domain Recommendation

Huishi Luo, Yiqing Wu, Yiwen Chen +2

Multi-domain recommendation leverages domain-general knowledge to improve recommendations across several domains. However, as platforms expand to dozens or hundreds of scenarios, t…