36 citations · 65 across the 13 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.IR2023★ 1 cited
FLIP: Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction
Hangyu Wang, Jianghao Lin, Xiangyang Li +5
Click-through rate (CTR) prediction plays as a core function module in various personalized online services. The traditional ID-based models for CTR prediction take as inputs the o…
cs.IR2023★ 1 cited
ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation
Jianghao Lin, Rong Shan, Chenxu Zhu +6
With large language models (LLMs) achieving remarkable breakthroughs in natural language processing (NLP) domains, LLM-enhanced recommender systems have received much attention and…
cs.IR2023★ 21 cited
How Can Recommender Systems Benefit from Large Language Models: A Survey
Jianghao Lin, Xinyi Dai, Yunjia Xi +11
With the rapid development of online services, recommender systems (RS) have become increasingly indispensable for mitigating information overload. Despite remarkable progress, con…