activity
20212025
most citedLearning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks

130 citations · 164 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025★ 2 cited

Enhancing Job Salary Prediction with Disentangled Composition Effect Modeling: A Neural Prototyping Approach

Yang Ji, Ying Sun, Hengshu Zhu

In the era of the knowledge economy, understanding how job skills influence salary is crucial for promoting recruitment with competitive salary systems and aligned salary expectati…

cs.LG2025★ 9 cited

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…

cs.IR2024★ 4 cited

Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation

Yuting Zhang, Yiqing Wu, Ruidong Han +7

Recommendation systems, which assist users in discovering their preferred items among numerous options, have served billions of users across various online platforms. Intuitively,…

cs.CY2023★ 19 cited

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…

cs.IR2021★ 130 cited

Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks

Yongchun Zhu, Ruobing Xie, Fuzhen Zhuang +5

Recently, embedding techniques have achieved impressive success in recommender systems. However, the embedding techniques are data demanding and suffer from the cold-start problem.…