4 papers
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…
Sequence-aware Large Language Models for Explainable Recommendation
Gangyi Zhang, Runzhe Teng, Chongming Gao
Large Language Models (LLMs) have shown strong potential in generating natural language explanations for recommender systems. However, existing methods often overlook the sequentia…
Reformulating Conversational Recommender Systems as Tri-Phase Offline Policy Learning
Gangyi Zhang, Chongming Gao, Hang Pan +2
Existing Conversational Recommender Systems (CRS) predominantly utilize user simulators for training and evaluating recommendation policies. These simulators often oversimplify the…
Leveraging LLMs for Influence Path Planning in Proactive Recommendation
Mingze Wang, Shuxian Bi, Wenjie Wang +3
Recommender systems are pivotal in Internet social platforms, yet they often cater to users' historical interests, leading to critical issues like echo chambers. To broaden user ho…