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 …

Domain specialization as the key to make large language models disruptive: A comprehensive survey

C Ling, X Zhao, J Lu, C Deng, C Zheng, J Wang… - arxiv preprint arxiv …, 2023 - arxiv.org
Large language models (LLMs) have significantly advanced the field of natural language
processing (NLP), providing a highly useful, task-agnostic foundation for a wide range of …

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 …

A survey on large language models for recommendation

L Wu, Z Zheng, Z Qiu, H Wang, H Gu, T Shen, C Qin… - World Wide Web, 2024 - Springer
Abstract Large Language Models (LLMs) have emerged as powerful tools in the field of
Natural Language Processing (NLP) and have recently gained significant attention in the …

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 …

Improved trust in human-robot collaboration with ChatGPT

Y Ye, H You, J Du - IEEE Access, 2023 - ieeexplore.ieee.org
Human-robot collaboration is becoming increasingly important as robots become more
involved in various aspects of human life in the era of Artificial Intelligence. However, the …

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 …

Collm: Integrating collaborative embeddings into large language models for recommendation

Y Zhang, F Feng, J Zhang, K Bao, Q Wang… - arxiv preprint arxiv …, 2023 - arxiv.org
Leveraging Large Language Models as Recommenders (LLMRec) has gained significant
attention and introduced fresh perspectives in user preference modeling. Existing LLMRec …

Llm-based edge intelligence: A comprehensive survey on architectures, applications, security and trustworthiness

O Friha, MA Ferrag, B Kantarci… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
The integration of Large Language Models (LLMs) and Edge Intelligence (EI) introduces a
groundbreaking paradigm for intelligent edge devices. With their capacity for human-like …

Beyond efficiency: A systematic survey of resource-efficient large language models

G Bai, Z Chai, C Ling, S Wang, J Lu, N Zhang… - arxiv preprint arxiv …, 2024 - arxiv.org
The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated
models like OpenAI's ChatGPT, represents a significant advancement in artificial …