22 citations · 22 across the 4 of their papers we have counts for
4 papers
MindRec: A Diffusion-driven Coarse-to-Fine Paradigm for Generative Recommendation
Mengyao Gao, Chongming Gao, Haoyan Liu +5
Recent advancements in large language model-based recommendation systems often represent items as text or semantic IDs and generate recommendations in an auto-regressive manner. Ho…
Process-Supervised LLM Recommenders via Flow-guided Tuning
Chongming Gao, Mengyao Gao, Chenxiao Fan +3
While large language models (LLMs) are increasingly adapted for recommendation systems via supervised fine-tuning (SFT), this approach amplifies popularity bias due to its likeliho…
SPRec: Self-Play to Debias LLM-based Recommendation
Chongming Gao, Ruijun Chen, Shuai Yuan +3
Large language models (LLMs) have attracted significant attention in recommendation systems. Current work primarily applies supervised fine-tuning (SFT) to adapt the model for reco…
DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender Systems
Jiaju Chen, Chongming Gao, Shuai Yuan +3
The integration of Large Language Models (LLMs) into recommender systems has led to substantial performance improvements. However, this often comes at the cost of diminished recomm…