80 citations · 222 across the 32 of their papers we have counts for
31 papers
RecAI: Leveraging Large Language Models for Next-Generation Recommender Systems
Jianxun Lian, Yuxuan Lei, Xu Huang +3
This paper introduces RecAI, a practical toolkit designed to augment or even revolutionize recommender systems with the advanced capabilities of Large Language Models (LLMs). RecAI…
High-Frequency-aware Hierarchical Contrastive Selective Coding for Representation Learning on Text-attributed Graphs
Peiyan Zhang, Chaozhuo Li, Liying Kang +4
We investigate node representation learning on text-attributed graphs (TAGs), where nodes are associated with text information. Although recent studies on graph neural networks (GN…
Ada-Retrieval: An Adaptive Multi-Round Retrieval Paradigm for Sequential Recommendations
Lei Li, Jianxun Lian, Xiao Zhou +1
Retrieval models aim at selecting a small set of item candidates which match the preference of a given user. They play a vital role in large-scale recommender systems since subsequ…
Knowledge Plugins: Enhancing Large Language Models for Domain-Specific Recommendations
Jing Yao, Wei Xu, Jianxun Lian +3
The significant progress of large language models (LLMs) provides a promising opportunity to build human-like systems for various practical applications. However, when applied to s…
Unpacking the Ethical Value Alignment in Big Models
Xiaoyuan Yi, Jing Yao, Xiting Wang +1
Big models have greatly advanced AI's ability to understand, generate, and manipulate information and content, enabling numerous applications. However, as these models become incre…
A Data-Centric Multi-Objective Learning Framework for Responsible Recommendation Systems
Xu Huang, Jianxun Lian, Hao Wang +2
Recommendation systems effectively guide users in locating their desired information within extensive content repositories. Generally, a recommendation model is optimized to enhanc…