Reformulating Sequential Recommendation: Bridging Language Models and Recommender Systems

The authors propose LANCER, a paradigm that integrates language models and recommender systems to provide personalized recommendations by leveraging domain-specific knowledge and item content. This approach aims to bridge the gap between language models and recommender systems.