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20232026
most citedOn the Opportunities of Green Computing: A Survey

9 citations · 26 across the 51 of their papers we have counts for

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Showing 2025 · cs.IRShow all

8 papers · 2 filters

cs.IR2025★ 1 cited

Empowering Denoising Sequential Recommendation with Large Language Model Embeddings

Tongzhou Wu, Yuhao Wang, Maolin Wang +2

Sequential recommendation aims to capture user preferences by modeling sequential patterns in user-item interactions. However, these models are often influenced by noise such as ac…

cs.IR2025★ 1 cited

SPARK: Adaptive Low-Rank Knowledge Graph Modeling in Hybrid Geometric Spaces for Recommendation

Binhao Wang, Yutian Xiao, Maolin Wang +4

Knowledge Graphs (KGs) enhance recommender systems but face challenges from inherent noise, sparsity, and Euclidean geometry's inadequacy for complex relational structures, critica…

cs.IR2025

Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs

Yuhao Wang, Junwei Pan, Xinhang Li +6

Sequential recommendation (SR) aims to capture users' dynamic interests and sequential patterns based on their historical interactions. Recently, the powerful capabilities of large…

cs.IR2025

FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation

Maolin Wang, Yutian Xiao, Binhao Wang +6

Modern recommendation systems face significant challenges in processing multimodal sequential data, particularly in temporal dynamics modeling and information flow coordination. Tr…

cs.IR2025

Measure Domain's Gap: A Similar Domain Selection Principle for Multi-Domain Recommendation

Yi Wen, Yue Liu, Derong Xu +9

Multi-Domain Recommendation (MDR) achieves the desirable recommendation performance by effectively utilizing the transfer information across different domains. Despite the great su…

cs.IR2025

STAR-Rec: Making Peace with Length Variance and Pattern Diversity in Sequential Recommendation

Maolin Wang, Sheng Zhang, Ruocheng Guo +6

Recent deep sequential recommendation models often struggle to effectively model key characteristics of user behaviors, particularly in handling sequence length variations and capt…

cs.IR2025

LSRP: A Leader-Subordinate Retrieval Framework for Privacy-Preserving Cloud-Device Collaboration

Yingyi Zhang, Pengyue Jia, Xianneng Li +8

Cloud-device collaboration leverages on-cloud Large Language Models (LLMs) for handling public user queries and on-device Small Language Models (SLMs) for processing private user d…

cs.IR2025

Behavior Modeling Space Reconstruction for E-Commerce Search

Yejing Wang, Chi Zhang, Xiangyu Zhao +8

Delivering superior search services is crucial for enhancing customer experience and driving revenue growth. Conventionally, search systems model user behaviors by combining user p…