1 Introduction
2 Modeling Paradigms and Taxonomy
3 Discriminative LLMs for Recommendation
3.1 Fine-tuning
3.2 Prompt Tuning
4 Generative LLMs for Recommendation
4.1 Non-tuning Paradigm
4.2 Tuning Paradigm
5 Findings
5.1 Model Bias
5.2 Recommendation Prompt Designing
5.3 Promising Ability
5.4 Evaluation Issues
6 Conclusion