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 …

[PDF][PDF] Natural language is all a graph needs

R Ye, C Zhang, R Wang, S Xu, Y Zhang - arxiv preprint arxiv …, 2023 - yongfeng.me
The emergence of large-scale pre-trained language models, such as ChatGPT, has
revolutionized various research fields in artificial intelligence. Transformersbased large …

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

J Lin, X Dai, Y **, W Liu, B Chen, H Zhang… - ACM Transactions on …, 2023 - dl.acm.org
With the rapid development of online services and web applications, recommender systems
(RS) have become increasingly indispensable for mitigating information overload and …

Data augmentation using llms: Data perspectives, learning paradigms and challenges

B Ding, C Qin, R Zhao, T Luo, X Li… - Findings of the …, 2024 - aclanthology.org
In the rapidly evolving field of large language models (LLMs), data augmentation (DA) has
emerged as a pivotal technique for enhancing model performance by diversifying training …

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 …

Prompt distillation for efficient llm-based recommendation

L Li, Y Zhang, L Chen - Proceedings of the 32nd ACM International …, 2023 - dl.acm.org
Large language models (LLM) have manifested unparalleled modeling capability on various
tasks, eg, multi-step reasoning, but the input to these models is mostly limited to plain text …

A survey on trustworthy recommender systems

Y Ge, S Liu, Z Fu, J Tan, Z Li, S Xu, Y Li, Y **an… - 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 …

Vip5: Towards multimodal foundation models for recommendation

S Geng, J Tan, S Liu, Z Fu, Y Zhang - arxiv preprint arxiv:2305.14302, 2023 - arxiv.org
Computer Vision (CV), Natural Language Processing (NLP), and Recommender Systems
(RecSys) are three prominent AI applications that have traditionally developed …

Let me do it for you: Towards llm empowered recommendation via tool learning

Y Zhao, J Wu, X Wang, W Tang, D Wang… - Proceedings of the 47th …, 2024 - dl.acm.org
Conventional recommender systems (RSs) face challenges in precisely capturing users' fine-
grained preferences. Large language models (LLMs) have shown capabilities in …