collaborators

5 papers

cs.IR2026

Zero-Observation User Reactivation with Gap-Driven Dimensional Gating

Jiandong Ding, Tianying Liu, Fuyuan Liu +2

Sequential recommendation (SR) models capture continuously observed behavior, but a returning user may have no interactions for months or years. We define this setting as Zero-Obse…

cs.IR2026

Right Family, Wrong Skill: Benchmarking Risk Exposure in Agent Skill Retrieval

Jiandong Ding, Honglei Ji, Ming Liu +1

Agent skill libraries are becoming routable software assets: a retrieved skill can contribute instructions, scripts, resource bindings, and execution assumptions to an agent. This…

cs.IR2026

SIDInspector: A Mapping-First Diagnostic Resource for Semantic-ID Tokenizers

Jiandong Ding, Heng Chang, Huijie Qin +1

Semantic-ID (SID) tokenizers are increasingly reused as standalone artifacts in generative recommendation: an exported item-to-code mapping becomes the address space that a later s…

cs.IR2026

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

Zerui Chen, Heng Chang, Tianying Liu +5

Generative Recommenders (GRs), exemplified by the Hierarchical Sequential Transduction Unit (HSTU), have emerged as a powerful paradigm for modeling long user interaction sequences…

cs.IR2025

Towards Practical Large-scale Dynamical Heterogeneous Graph Embedding: Cold-start Resilient Recommendation

Mabiao Long, Jiaxi Liu, Yufeng Li +5

Deploying dynamic heterogeneous graph embeddings in production faces key challenges of scalability, data freshness, and cold-start. This paper introduces a practical, two-stage sol…