From the 1 of 7 linked papers with an AI index.
7 papers
CogRec: Structure-Cognitive Fast-and-Slow Reasoning for Generative Recommendation
Xiang Liu, Jingsong Su, Shuqi Zhao +7
Semantic-ID-based generative recommendation represents each item as a hierarchical discrete token sequence and reformulates next-item prediction as constrained sequence generation.…
Can We Steer the Black-Box? Towards Controllability-Centric Evaluation of Recommender Systems with Collaborative Agents
Jiwen Zhou, Xiang Liu, Mingming Li +5
The paper introduces CtrlBench-Rec, a collaborative multi‑agent framework for evaluating how controllable recommender systems are, focusing on tasks such as target content discover…
HoloRec: Holistic Encoding and Interleaved Reasoning for Generative Recommendation
Shuqi Zhao, Jingsong Su, Xiang Liu +9
Generative recommendation models that formulate the task as sequence generation overcome the objective fragmentation problem of traditional cascade architectures, yet existing appr…
BAHSD: Bridging the Long-tail Gap via Adaptive Distillation in Black-box Sequential Recommendation
Xi Zhou, Famin Wu, Mingming Li +4
Sequential recommendation systems are widely adopted but often deployed as black-box APIs, which has driven recent interest in model extraction to replicate their capabilities loca…
RecBundle: A Next-Generation Geometric Paradigm for Explainable Recommender Systems
Hui Wang, Tianzhu Hu, Mingming Li +6
Recommender systems are inherently dynamic feedback loops where prolonged local interactions accumulate into macroscopic structural degradation such as information cocoons. Existin…
A Cognitive Distribution and Behavior-Consistent Framework for Black-Box Attacks on Recommender Systems
Hongyue Zhang, Mingming Li, Dongqin Liu +6
With the growing deployment of sequential recommender systems in e-commerce and other fields, their black-box interfaces raise security concerns: models are vulnerable to extractio…