Recommender systems in the era of large language models (llms)

Z Zhao, W Fan, J Li, Y Liu, X Mei, Y Wang… - arXiv preprint arXiv …, 2023 - arxiv.org
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an important component of our daily life, providing personalized suggestions …

Recommender systems in the era of large language models (llms)

Z Zhao, W Fan, J Li, Y Liu, X Mei… - … on Knowledge and …, 2024 - ieeexplore.ieee.org
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an indispensable and important component in our daily lives, providing …

Large language models for generative recommendation: A survey and visionary discussions

L Li, Y Zhang, D Liu, L Chen - arXiv preprint arXiv:2309.01157, 2023 - arxiv.org
Recent years have witnessed the wide adoption of large language models (LLM) in different
fields, especially natural language processing and computer vision. Such a trend can also …

A survey on trustworthy recommender systems

Y Ge, S Liu, Z Fu, J Tan, Z Li, S Xu, Y Li, Y Xian… - ACM Transactions on …, 2024 - dl.acm.org
Recommender systems (RS), serving at the forefront of Human-centered AI, are widely
deployed in almost every corner of the web and facilitate the human decision-making …

Idgenrec: Llm-recsys alignment with textual id learning

J Tan, S Xu, W Hua, Y Ge, Z Li, Y Zhang - Proceedings of the 47th …, 2024 - dl.acm.org
LLM-based Generative recommendation has attracted significant attention. However, in
contrast to standard NLP tasks that inherently operate on human vocabulary, current …

Securing large language models: Addressing bias, misinformation, and prompt attacks

B Peng, K Chen, M Li, P Feng, Z Bi, J Liu… - arXiv preprint arXiv …, 2024 - arxiv.org
Large Language Models (LLMs) demonstrate impressive capabilities across various fields,
yet their increasing use raises critical security concerns. This article reviews recent literature …

How can recommender systems benefit from large language models: A survey

J Lin, X Dai, Y Xi, W Liu, B Chen, H Zhang, Y Liu… - arXiv preprint arXiv …, 2023 - arxiv.org
With the rapid development of online services, recommender systems (RS) have become
increasingly indispensable for mitigating information overload. Despite remarkable …

Recranker: Instruction tuning large language model as ranker for top-k recommendation

S Luo, B He, H Zhao, W Shao, Y Qi, Y Huang… - ACM Transactions on …, 2023 - dl.acm.org
Large Language Models (LLMs) have demonstrated remarkable capabilities and have been
extensively deployed across various domains, including recommender systems. Prior …

Llara: Aligning large language models with sequential recommenders

J Liao, S Li, Z Yang, J Wu, Y Yuan, X Wang… - arXiv preprint arXiv …, 2023 - arxiv.org
Sequential recommendation aims to predict the subsequent items matching user preference
based on her/his historical interactions. With the development of Large Language Models …

E4srec: An elegant effective efficient extensible solution of large language models for sequential recommendation

X Li, C Chen, X Zhao, Y Zhang, C Xing - arXiv preprint arXiv:2312.02443, 2023 - arxiv.org
The recent advancements in Large Language Models (LLMs) have sparked interest in
harnessing their potential within recommender systems. Since LLMs are designed for …