Chenglei Shen

Personalized large language models (LLMs) adapt model behavior to individual users to enhance user satisfaction, yet personalization can inadvertently distort factual reasoning. We show that when personalized LLMs face factual queries, there exists a phenomenon where the model generates answers a...

Generative recommendation (GR) has demonstrated substantial potential for sequential recommendation in an end-to-end generation paradigm. However, existing models suffer from severe cold-start collapse, i.e., recommendation accuracy on cold-start items drops to near zero. Current solutions rely o...