Jianfeng Deng

Logit Space Constrained Fine-Tuning for Mitigating Hallucinations in LLM-Based Recommender Systems

Large language models (LLMs) have gained increasing attention in recommender systems, but their inherent hallucination issues significantly compromise the accuracy and reliability of recommendation results. Existing LLM-based recommender systems predominantly rely on standard fine-tuning methodologi