NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (14)

cs.LG2024

Entropy Law: The Story Behind Data Compression and LLM Performance

Mingjia Yin, Chuhan Wu, Yufei Wang +7

cs.LG2026

Understanding DNNs in Feature Interaction Models: A Dimensional Collapse Perspective

Jiancheng Wang, Mingjia Yin, Hao Wang +1

cs.IR2024

A Unified Framework for Adaptive Representation Enhancement and Inversed Learning in Cross-Domain Recommendation

Luankang Zhang, Hao Wang, Suojuan Zhang +5

cs.IR2024

Dataset Regeneration for Sequential Recommendation

Mingjia Yin, Hao Wang, Wei Guo +5

cs.IR2026

Why Thinking Hurts: Diagnosing and Rectifying Linguistic Inertia in Large Language Models for Recommendation

Luankang Zhang, Yonghao Huang, Hang Lv +6

cs.IR2026

DIET: Learning to Distill Dataset Continually for Recommender Systems

Jiaqing Zhang, Hao Wang, Mingjia Yin +6

cs.IR2025

From Feature Interaction to Feature Generation: A Generative Paradigm of CTR Prediction Models

Mingjia Yin, Junwei Pan, Hao Wang +5

cs.AI2026

Generative Data Transformation: From Mixed to Unified Data

Jiaqing Zhang, Mingjia Yin, Hao Wang +6

cs.IR2025

Enhancing CTR Prediction with De-correlated Expert Networks

Jiancheng Wang, Mingjia Yin, Hao Wang +1

cs.IR2026

Can Recommender Systems Teach Themselves? A Recursive Self-Improving Framework with Fidelity Control

Luankang Zhang, Hao Wang, Zhongzhou Liu +8

cs.IR2024

MDAP: A Multi-view Disentangled and Adaptive Preference Learning Framework for Cross-Domain Recommendation

Junxiong Tong, Mingjia Yin, Hao Wang +3

cs.IR2024

Learning Partially Aligned Item Representation for Cross-Domain Sequential Recommendation

Mingjia Yin, Hao Wang, Wei Guo +6

cs.IR2023

APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation

Mingjia Yin, Hao Wang, Xiang Xu +7

cs.IR2025

TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendation

Jiaqing Zhang, Mingjia Yin, Hao Wang +5