WWW 2026 / Recommender Systems

Beyond the Flat Sequence: Hierarchical and Preference-Aware Generative Recommendations

A generative recommendation paper that studies hierarchical structure and preference-aware modeling beyond flat user-history sequences.

Research area

User reactivation, generative recommendation, dynamic retrieval, graph embedding, counterfactual watch-time prediction, and efficient CTR modeling form the main technical line.

Publication record

Authors
Z Chen, H Chang, T Liu, C Zhou, Y Cao, J Ding, M Liu, B Qin
Venue
Proceedings of the ACM Web Conference 2026
Year
2026
Area
Recommender Systems