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 …

[HTML][HTML] A survey on large language model (llm) security and privacy: The good, the bad, and the ugly

Y Yao, J Duan, K Xu, Y Cai, Z Sun, Y Zhang - High-Confidence Computing, 2024 - Elsevier
Abstract Large Language Models (LLMs), such as ChatGPT and Bard, have revolutionized
natural language understanding and generation. They possess deep language …

Interactive natural language processing

Z Wang, G Zhang, K Yang, N Shi, W Zhou… - arXiv preprint arXiv …, 2023 - arxiv.org
Interactive Natural Language Processing (iNLP) has emerged as a novel paradigm within
the field of NLP, aimed at addressing limitations in existing frameworks while aligning with …

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 …

Llmaaa: Making large language models as active annotators

R Zhang, Y Li, Y Ma, M Zhou, L Zou - arXiv preprint arXiv:2310.19596, 2023 - arxiv.org
Prevalent supervised learning methods in natural language processing (NLP) are
notoriously data-hungry, which demand large amounts of high-quality annotated data. In …

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 …

Risk taxonomy, mitigation, and assessment benchmarks of large language model systems

T Cui, Y Wang, C Fu, Y Xiao, S Li, X Deng, Y Liu… - arXiv preprint arXiv …, 2024 - arxiv.org
Large language models (LLMs) have strong capabilities in solving diverse natural language
processing tasks. However, the safety and security issues of LLM systems have become the …

On protecting the data privacy of large language models (llms): A survey

B Yan, K Li, M Xu, Y Dong, Y Zhang, Z Ren… - arXiv preprint arXiv …, 2024 - arxiv.org
Large language models (LLMs) are complex artificial intelligence systems capable of
understanding, generating and translating human language. They learn language patterns …

Future trends in smart green iov: Vehicle-to-everything in the era of electric vehicles

T Aldhanhani, A Abraham… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
The electrification of the transportation sector is a pivotal stride towards ensuring
sustainability in our systems. This paradigm offers a promising solution to multiple …

Differentially private natural language models: Recent advances and future directions

L Hu, I Habernal, L Shen, D Wang - arXiv preprint arXiv:2301.09112, 2023 - arxiv.org
Recent developments in deep learning have led to great success in various natural
language processing (NLP) tasks. However, these applications may involve data that …