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 …

When large language models meet personalization: Perspectives of challenges and opportunities

J Chen, Z Liu, X Huang, C Wu, Q Liu, G Jiang, Y Pu… - World Wide Web, 2024 - Springer
The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …

A survey of large language models

WX Zhao, K Zhou, J Li, T Tang, X Wang, Y Hou… - arXiv preprint arXiv …, 2023 - arxiv.org
Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

Large language models are zero-shot rankers for recommender systems

Y Hou, J Zhang, Z Lin, H Lu, R Xie, J McAuley… - … on Information Retrieval, 2024 - Springer
Recently, large language models (LLMs)(eg, GPT-4) have demonstrated impressive general-
purpose task-solving abilities, including the potential to approach recommendation tasks …

Recommendation as instruction following: A large language model empowered recommendation approach

J Zhang, R Xie, Y Hou, X Zhao, L Lin… - ACM Transactions on …, 2023 - dl.acm.org
In the past decades, recommender systems have attracted much attention in both research
and industry communities. Existing recommendation models mainly learn the underlying …

Towards open-world recommendation with knowledge augmentation from large language models

Y Xi, W Liu, J Lin, X Cai, H Zhu, J Zhu, B Chen… - Proceedings of the 18th …, 2024 - dl.acm.org
Recommender system plays a vital role in various online services. However, its insulated
nature of training and deploying separately within a specific closed domain limits its access …

Large language models for generative information extraction: A survey

D Xu, W Chen, W Peng, C Zhang, T Xu, X Zhao… - Frontiers of Computer …, 2024 - Springer
Abstract Information Extraction (IE) aims to extract structural knowledge from plain natural
language texts. Recently, generative Large Language Models (LLMs) have demonstrated …

Llara: Large language-recommendation assistant

J Liao, S Li, Z Yang, J Wu, Y Yuan, X Wang… - Proceedings of the 47th …, 2024 - dl.acm.org
Sequential recommendation aims to predict users' next interaction with items based on their
past engagement sequence. Recently, the advent of Large Language Models (LLMs) has …

Adapting large language models by integrating collaborative semantics for recommendation

B Zheng, Y Hou, H Lu, Y Chen, WX Zhao… - 2024 IEEE 40th …, 2024 - ieeexplore.ieee.org
Recently, large language models (LLMs) have shown great potential in recommender
systems, either improving existing recommendation models or serving as the backbone …

Look before you leap: An exploratory study of uncertainty measurement for large language models

Y Huang, J Song, Z Wang, S Zhao, H Chen… - arXiv preprint arXiv …, 2023 - arxiv.org
The recent performance leap of Large Language Models (LLMs) opens up new
opportunities across numerous industrial applications and domains. However, erroneous …