7 papers
Rethinking Popularity Bias in Collaborative Filtering via Analytical Vector Decomposition
Lingfeng Liu, Yixin Song, Dazhong Shen +4
Popularity bias fundamentally undermines the personalization capabilities of collaborative filtering (CF) models, causing them to disproportionately recommend popular items while n…
Enhancing Conversational Recommender Systems with Tree-Structured Knowledge and Pretrained Language Models
Yongwen Ren, Chao Wang, Peng Du +3
Recent advances in pretrained language models (PLMs) have significantly improved conversational recommender systems (CRS), enabling more fluent and context-aware interactions. To f…
FACE: A General Framework for Mapping Collaborative Filtering Embeddings into LLM Tokens
Chao Wang, Yixin Song, Jinhui Ye +5
Recently, large language models (LLMs) have been explored for integration with collaborative filtering (CF)-based recommendation systems, which are crucial for personalizing user e…
A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics
Chuan Qin, Le Zhang, Yihang Cheng +8
In today's competitive and fast-evolving business environment, it is a critical time for organizations to rethink how to make talent-related decisions in a quantitative manner. Ind…
A Comprehensive Survey on Self-Interpretable Neural Networks
Yang Ji, Ying Sun, Yuting Zhang +7
Neural networks have achieved remarkable success across various fields. However, the lack of interpretability limits their practical use, particularly in critical decision-making s…
Boosting Knowledge Graph-based Recommendations through Confidence-Aware Augmentation with Large Language Models
Rui Cai, Chao Wang, Qianyi Cai +2
Knowledge Graph-based recommendations have gained significant attention due to their ability to leverage rich semantic relationships. However, constructing and maintaining Knowledg…