42 citations · 127 across the 41 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.IR2023★ 1 cited
Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems
Tianhao Shi, Yang Zhang, Zhijian Xu +4
Adapting Large Language Models for Recommendation (LLM4Rec) has shown promising results. However, the challenges of deploying LLM4Rec in real-world scenarios remain largely unexplo…
cs.CL2023★ 3 cited
Attack Prompt Generation for Red Teaming and Defending Large Language Models
Boyi Deng, Wenjie Wang, Fuli Feng +3
Large language models (LLMs) are susceptible to red teaming attacks, which can induce LLMs to generate harmful content. Previous research constructs attack prompts via manual or au…
cs.IR2023★ 1 cited
RecAD: Towards A Unified Library for Recommender Attack and Defense
Changsheng Wang, Jianbai Ye, Wenjie Wang +3
In recent years, recommender systems have become a ubiquitous part of our daily lives, while they suffer from a high risk of being attacked due to the growing commercial and social…