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20232026
most citedEnhancing Recommender Systems with Large Language Model Reasoning Graphs

13 citations · 42 across the 18 of their papers we have counts for

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5 papers · 1 filter

cs.AI2023★ 1 cited

Making Large Language Models Better Knowledge Miners for Online Marketing with Progressive Prompting Augmentation

Chunjing Gan, Dan Yang, Binbin Hu +6

Nowadays, the rapid development of mobile economy has promoted the flourishing of online marketing campaigns, whose success greatly hinges on the efficient matching between user pr…

cs.CL2023★ 7 cited

Think-in-Memory: Recalling and Post-thinking Enable LLMs with Long-Term Memory

Lei Liu, Xiaoyan Yang, Yue Shen +4

Memory-augmented Large Language Models (LLMs) have demonstrated remarkable performance in long-term human-machine interactions, which basically relies on iterative recalling and re…

cs.IR2023★ 11 cited

Leveraging Large Language Models for Pre-trained Recommender Systems

Zhixuan Chu, Hongyan Hao, Xin Ouyang +9

Recent advancements in recommendation systems have shifted towards more comprehensive and personalized recommendations by utilizing large language models (LLM). However, effectivel…

cs.IR2023★ 13 cited

Enhancing Recommender Systems with Large Language Model Reasoning Graphs

Yan Wang, Zhixuan Chu, Xin Ouyang +10

Recommendation systems aim to provide users with relevant suggestions, but often lack interpretability and fail to capture higher-level semantic relationships between user behavior…

cs.LG2023★ 1 cited

Who Would be Interested in Services? An Entity Graph Learning System for User Targeting

Dan Yang, Binbin Hu, Xiaoyan Yang +4

With the growing popularity of various mobile devices, user targeting has received a growing amount of attention, which aims at effectively and efficiently locating target users th…