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20242026
most citedGraph Machine Learning in the Era of Large Language Models (LLMs)

5 citations · 6 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.IR2026

Atomic Intent Reasoning: Bringing LLM Semantics to Industrial Cross-Domain Recommendations

Zhuohang Jiang, Yuxin Chen, Shijie Wang +6

Cross-domain recommendation is a core problem in content-to-e-commerce platforms. Its objective is to leverage user interactions with content to infer potential purchasing intent o…

cs.IR2026

ReRec: Reasoning-Augmented LLM-based Recommendation Assistant via Reinforcement Fine-tuning

Jiani Huang, Shijie Wang, Liangbo Ning +2

With the rise of LLMs, there is an increasing need for intelligent recommendation assistants that can handle complex queries and provide personalized, reasoning-driven recommendati…

cs.IR20261 cited

Towards Next-Generation Recommender Systems: A Benchmark for Personalized Recommendation Assistant with LLMs

Jiani Huang, Shijie Wang, Liang-bo Ning +4

Recommender systems (RecSys) are widely used across various modern digital platforms and have garnered significant attention. Traditional recommender systems usually focus only on…

cs.IR2025

Continuous-time Discrete-space Diffusion Model for Recommendation

Chengyi Liu, Xiao Chen, Shijie Wang +2

In the era of information explosion, Recommender Systems (RS) are essential for alleviating information overload and providing personalized user experiences. Recent advances in dif…

cs.IR2025

Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation

Shijie Wang, Wenqi Fan, Yue Feng +4

Recommender systems have become increasingly vital in our daily lives, helping to alleviate the problem of information overload across various user-oriented online services. The em…