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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:

Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation
Jizhi Zhang, Keqin Bao, Yang Zhang, et al.
(2023), pp. 993-999
Open Access | Times Cited: 58

Showing 1-25 of 58 citing articles:

TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation
Keqin Bao, Jizhi Zhang, Yang Zhang, et al.
(2023), pp. 1007-1014
Open Access | Times Cited: 114
Large Language Models are Zero-Shot Rankers for Recommender Systems
Yupeng Hou, Junjie Zhang, Zihan Lin, et al.
Lecture notes in computer science (2024), pp. 364-381
Closed Access | Times Cited: 88
Recommender Systems in the Era of Large Language Models (LLMs)
Zihuai Zhao, Wenqi Fan, Jiatong Li, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 11, pp. 6889-6907
Open Access | Times Cited: 81
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: 65
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)
Yashar Deldjoo, Zhankui He, Julian McAuley, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 6448-6458
Open Access | Times Cited: 18
CFaiRLLM: Consumer Fairness Evaluation in Large-Language Model Recommender System
Yashar Deldjoo, Tommaso Di Noia
ACM Transactions on Intelligent Systems and Technology (2025)
Closed Access | Times Cited: 3
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 | Times Cited: 2
Understanding Biases in ChatGPT-based Recommender Systems: Provider Fairness, Temporal Stability, and Recency
Yashar Deldjoo
ACM Transactions on Recommender Systems (2024)
Open Access | Times Cited: 15
Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era
Sunhao Dai, Xu Chen, Shicheng Xu, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 6437-6447
Open Access | Times Cited: 11
LLM-Based Edge Intelligence: A Comprehensive Survey on Architectures, Applications, Security and Trustworthiness
Othmane Friha, Mohamed Amine Ferrag, Burak Kantarcı, et al.
IEEE Open Journal of the Communications Society (2024) Vol. 5, pp. 5799-5856
Open Access | Times Cited: 11
Item-side Fairness of Large Language Model-based Recommendation System
Meng Jiang, Keqin Bao, Jizhi Zhang, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 4717-4726
Open Access | Times Cited: 9
Large Language Models for Recommendation: Progresses and Future Directions
Jizhi Zhang, Keqin Bao, Yang Zhang, et al.
(2024), pp. 1268-1271
Open Access | Times Cited: 5
Data science for next-generation recommender systems
Shoujin Wang, Yan Wang, Fikret Sivrikaya, et al.
International Journal of Data Science and Analytics (2023) Vol. 16, Iss. 2, pp. 135-145
Open Access | Times Cited: 10
Large Language Models for Recommendation: Progresses and Future Directions
Keqin Bao, Jizhi Zhang, Yang Zhang, et al.
(2023)
Closed Access | Times Cited: 10
LangFair: A Python Package for Assessing Bias and Fairness in Large Language Model Use Cases
Dylan Bouchard, Mohit Singh Chauhan, David Skarbrevik, et al.
The Journal of Open Source Software (2025) Vol. 10, Iss. 105, pp. 7570-7570
Open Access
CTRL: Connect Collaborative and Language Model for CTR Prediction
Xiangyang Li, Bo Chen, Lu Hou, et al.
ACM Transactions on Recommender Systems (2025)
Open Access
A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems
Keqin Bao, Jizhi Zhang, Wenjie Wang, et al.
ACM Transactions on Recommender Systems (2025)
Open Access
Fairness identification of large language models in recommendation
Wei Liu, Baisong Liu, Jiangcheng Qin, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Unifying Bias and Unfairness in Information Retrieval: New Challenges in the LLM Era
Sunhao Dai, Xu Chen, Shicheng Xu, et al.
(2025), pp. 998-1001
Closed Access
MMAgentRec, a personalized multi-modal recommendation agent with large language model
Xiaochen Xiao
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
SPRec: Self-Play to Debias LLM-based Recommendation
Chongming Gao, Renqiang Chen, Shuai Yuan, et al.
(2025), pp. 5075-5084
Closed Access
Multi-Prompting Scenario-based Movie Recommendation with Large Language Models: Real User Case Study
Ruixuan Sun, Xinyi Li, Avinash Akella, et al.
(2025), pp. 1-12
Closed Access
DyBooster: Leveraging large language model as booster for dynamic recommendation
Haoran Tang, Xueyao Sun, Shiqing Wu, et al.
Expert Systems with Applications (2025) Vol. 286, pp. 128080-128080
Closed Access
Hierarchical Sequence ID Representation of Large Language Models for Large-scale Recommendation Systems
Rui Zhao, Rui Zhong, Haoran Zheng, et al.
(2025), pp. 641-650
Closed Access
RALLRec: Improving Retrieval Augmented Large Language Model Recommendation with Representation Learning
Jian Xu, Sichun Luo, Xiangyu Chen, et al.
(2025), pp. 1436-1440
Open Access
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