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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Representation Learning with Large Language Models for Recommendation
Xubin Ren, Wei Wei, Lianghao Xia, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 3464-3475
Open Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

A survey on large language models for recommendation
Likang Wu, Zhi Zheng, Zhaopeng Qiu, et al.
World Wide Web (2024) Vol. 27, Iss. 5
Closed Access | Times Cited: 41
Data-efficient Fine-tuning for LLM-based Recommendation
Xinyu Lin, Wenjie Wang, Yongqi Li, et al.
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2024), pp. 365-374
Open Access | Times Cited: 19
UrbanGPT: Spatio-Temporal Large Language Models
Zhonghang Li, Lianghao Xia, Jiabin Tang, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 5351-5362
Open Access | Times Cited: 10
Result Diversification in Search and Recommendation: A Survey
Haolun Wu, Yansen Zhang, Chen Ma, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 10, pp. 5354-5373
Open Access | Times Cited: 6
DCRLRec: Dual-domain contrastive reinforcement large language model for recommendation
Zijian Bai, Zheng Yong, Peng Yang, et al.
Information Processing & Management (2025) Vol. 62, Iss. 4, pp. 104140-104140
Closed Access
In-depth survey: deep learning in recommender systems—exploring prediction and ranking models, datasets, feature analysis, and emerging trends
Shivangi Gheewala, Shuxiang Xu, Soonja Yeom
Neural Computing and Applications (2025)
Open Access
Revisiting explicit recommendation with DC-GCN: Divide-and-Conquer Graph Convolution Network
Furong Peng, Fujin Liao, Xuan Lu, et al.
Information Systems (2025), pp. 102513-102513
Closed Access
Comprehend Then Predict: Prompting Large Language Models for Recommendation with Semantic and Collaborative Data
Zhiang Dong, Liya Hu, Jingyuan Chen, et al.
ACM transactions on office information systems (2025)
Closed Access
LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework
Yiran Qiao, Xiang Ao, Yang Liu, et al.
(2025), pp. 232-241
Closed Access
A Contrastive Framework with User, Item and Review Alignment for Recommendation
Haizhen Dong, Yuan Fang, Hady W. Lauw
(2025), pp. 117-126
Closed Access
A Group Recommendation Method based on Automatically Integrating Members' Preferences via Taking Advantages of LLM
Shanshan Feng, Zhaobo Lang, Jing He, et al.
Information Sciences (2025), pp. 122067-122067
Closed Access
Profiling users with tag-enhanced spherical metric learning for recommendation
Yanchao Tan, Hang Lv, Xinyi Huang, et al.
International Journal of Machine Learning and Cybernetics (2025)
Closed Access
Towards improved recycling interventions: a multitasking model for consumer behavior analysis and segmentation
Feihong Xia, Jing Jian Xiao, Jing Wu
Journal of Marketing Analytics (2025)
Closed Access
Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models
Yunjia Xi, Weiwen Liu, Jianghao Lin, et al.
ACM Transactions on Recommender Systems (2025)
Open Access
Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis
Lanling Xu, Junjie Zhang, B. Li, et al.
ACM Transactions on Knowledge Discovery from Data (2025)
Closed Access
A Survey of Large Language Models for Graphs
Xubin Ren, Jiabin Tang, Dawei Yin, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 6616-6626
Open Access | Times Cited: 2
When Search Engine Services meet Large Language Models: Visions and Challenges
Haoyi Xiong, 将尚 渡辺, Yuchen Li, et al.
IEEE Transactions on Services Computing (2024) Vol. 17, Iss. 6, pp. 4558-4577
Open Access | Times Cited: 2
Denoising Alignment with Large Language Model for Recommendation
Yingtao Peng, Chen Gao, Yu Zhang, et al.
ACM transactions on office information systems (2024)
Closed Access | Times Cited: 1
Learnable Item Tokenization for Generative Recommendation
Wenjie Wang, Honghui Bao, Xinyu Lin, et al.
(2024), pp. 2400-2409
Open Access | Times Cited: 1
Enhancing E-Commerce Recommendation Systems with Multiple Item Purchase Data: A Bidirectional Encoder Representations from Transformers-Based Approach
Minseo Park, Jangmin Oh
Applied Sciences (2024) Vol. 14, Iss. 16, pp. 7255-7255
Open Access
CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation
Junda Wu, Cheng-Chun Chang, Tong Yu, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 3391-3401
Open Access
Fairness and Transparency in Music Recommender Systems: Improvements for Artists
Karlijn Dinnissen
(2024), pp. 1368-1375
Open Access
ReLand: Integrating Large Language Models' Insights into Industrial Recommenders via a Controllable Reasoning Pool
Changxin Tian, Binbin Hu, Chunjing Gan, et al.
(2024), pp. 63-73
Open Access
Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Models
Cui Yu, Feng Liu, P. Wang, et al.
(2024), pp. 507-517
Open Access
Sequential recommendation by reprogramming pretrained transformer
Min Tang, Shujie Cui, Zhe Jin, et al.
Information Processing & Management (2024) Vol. 62, Iss. 1, pp. 103938-103938
Closed Access
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