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20232026
most citedLinRec: Linear Attention Mechanism for Long-term Sequential Recommender Systems

86 citations · 252 across the 39 of their papers we have counts for

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Showing 2025Show all

15 papers · 1 filter

cs.CV2025

Renormalization Group Guided Tensor Network Structure Search

Maolin Wang, Bowen Yu, Sheng Zhang +8

Tensor network structure search (TN-SS) aims to automatically discover optimal network topologies and rank configurations for efficient tensor decomposition in high-dimensional dat…

cs.IR2025

BlossomRec: Block-level Fused Sparse Attention Mechanism for Sequential Recommendations

Mengyang Ma, Xiaopeng Li, Wanyu Wang +9

Transformer structures have been widely used in sequential recommender systems (SRS). However, as user interaction histories increase, computational time and memory requirements al…

cs.CL2025

MTA: A Merge-then-Adapt Framework for Personalized Large Language Model

Xiaopeng Li, Yuanjin Zheng, Wanyu Wang +6

Personalized Large Language Models (PLLMs) aim to align model outputs with individual user preferences, a crucial capability for user-centric applications. However, the prevalent a…

cs.IR2025

Democratic Recommendation with User and Item Representatives Produced by Graph Condensation

Jiahao Liang, Haoran Yang, Xiangyu Zhao +4

The challenges associated with large-scale user-item interaction graphs have attracted increasing attention in graph-based recommendation systems, primarily due to computational in…

cs.IR2025

LLM-EDT: Large Language Model Enhanced Cross-domain Sequential Recommendation with Dual-phase Training

Ziwei Liu, Qidong Liu, Wanyu Wang +6

Cross-domain Sequential Recommendation (CDSR) has been proposed to enrich user-item interactions by incorporating information from various domains. Despite current progress, the im…

cs.AI2025

Data Efficient Adaptation in Large Language Models via Continuous Low-Rank Fine-Tuning

Xiao Han, Zimo Zhao, Wanyu Wang +4

Recent advancements in Large Language Models (LLMs) have emphasized the critical role of fine-tuning (FT) techniques in adapting LLMs to specific tasks, especially when retraining…

cs.LG2025

PAINET: A Principled Efficient Transformer for 3D Dynamics Modeling

Kai Yang, Yuqi Huang, Junheng Tao +2

Modeling 3D dynamics is a fundamental problem in multi-body systems across scientific and engineering domains and has important practical implications in object trajectory predicti…

cs.LG2025

DANCE: Resource-Efficient Neural Architecture Search with Data-Aware and Continuous Adaptation

Maolin Wang, Tianshuo Wei, Sheng Zhang +6

Neural Architecture Search (NAS) has emerged as a powerful approach for automating neural network design. However, existing NAS methods face critical limitations in real-world depl…

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★ 4 cited

Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems

Langming Liu, Wanyu Wang, Chi Zhang +6

Online advertising in recommendation platforms has gained significant attention, with a predominant focus on channel recommendation and budget allocation strategies. However, curre…

cs.AI2025

Model Merging for Knowledge Editing

Zichuan Fu, Xian Wu, Guojing Li +6

Large Language Models (LLMs) require continuous updates to maintain accurate and current knowledge as the world evolves. While existing knowledge editing approaches offer various s…

cs.CL2025

Training-free LLM Merging for Multi-task Learning

Zichuan Fu, Xian Wu, Yejing Wang +6

Large Language Models (LLMs) have demonstrated exceptional capabilities across diverse natural language processing (NLP) tasks. The release of open-source LLMs like LLaMA and Qwen…

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.CL2025

Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression

Jingyu Peng, Maolin Wang, Nan Wang +7

Despite substantial advancements in aligning large language models (LLMs) with human values, current safety mechanisms remain susceptible to jailbreak attacks. We hypothesize that…

cs.IR2025★ 2 cited

A Survey of Personalization: From RAG to Agent

Xiaopeng Li, Pengyue Jia, Derong Xu +11

Personalization has become an essential capability in modern AI systems, enabling customized interactions that align with individual user preferences, contexts, and goals. Recent r…