9 papers
RECAP: Feedback-Driven Streaming Semantic User Profiles for Short-Video Recommendation
Ziyi Zhao, Xiaoyou Zhou, Xiao Lv +13
Language-based user profiles convert long behavioral histories into explicit semantic representations for recommendation. However, most profile generators are optimized in an open…
The Pitfall of Scaling Up: Uncovering and Mitigating Popularity Bias Amplification in Scaling Transformer-based Recommenders
Weiqin Yang, Yue Pan, Chongming Gao +4
We identify a critical pitfall in scaling transformer-based sequential recommenders: while increasing model size improves recommendation accuracy, it simultaneously amplifies popul…
Trustworthy Recommendation in the Era of Large Language Models: Opportunities and Challenges
Bohao Wang, Yu Cui, Zhenxiang Xu +13
The field of recommender systems (RS) is currently undergoing two profound paradigm shifts. From the perspective of objectives, the goal has shifted beyond mere recommendation accu…
Breaking User-Centric Agency: A Tri-Party Framework for Agent-Based Recommendation
Yaxin Gong, Chongming Gao, Chenxiao Fan +6
Large language models (LLMs) have spurred interest in agent-based recommender systems, yet most agentic approaches remain user-centric: items stay passive entities whose exposure i…
Beyond Static Best-of-N: Bayesian List-wise Alignment for LLM-based Recommendation
Ruijun Chen, Chongming Gao, Jiawei Chen +2
Large Language Models have revolutionized recommender systems (LLM4Rec) by leveraging their generative capabilities to model complex user preferences. However, existing LLM4Rec met…
Position-Aware Drafting for Inference Acceleration in LLM-Based Generative List-Wise Recommendation
Jiaju Chen, Chongming Gao, Chenxiao Fan +4
Large language model (LLM)-based generative list-wise recommendation has advanced rapidly, but decoding remains sequential and thus latency-prone. To accelerate inference without c…