Adapting Language Modeling Paradigms to Enhance Recommender Systems: Opportunities, Challenges, and Ethical Considerations

The adaptation of language modeling paradigms, such as pre-training, prompting, and optimization objectives, can significantly enhance the performance and trustworthiness of recommender systems by leveraging nuanced textual representations and extensive external knowledge.