3 papers
cs.IR2026
An LLM-Powered Semantic Alignment Framework for Journal Recommendation
Yanglin Yan, Zicheng Xie, Tianchen Gao +2
Journal recommendation is an important task in scholarly information systems. Existing approaches typically rely on supervised learning models, manually engineered features, or his…
stat.AP2026
Are Large Language Models able to Predict Highly Cited Papers? Evidence from Statistical Publications
Zhanshuo Ye, Yiming Hou, Rui Pan +2
Predicting highly-cited papers is a long-standing challenge due to the complex interactions of research content, scholarly communities, and temporal dynamics. Recent advances in la…
stat.AP2025
Academic Literature Recommendation in Large-scale Citation Networks Enhanced by Large Language Models
Kun Liu, Yan Zhang, Rui Pan +2
Literature recommendation is essential for researchers to find relevant articles in an ever-growing academic field. However, traditional methods often struggle due to data limitati…