Could Small Language Models Serve as Recommenders? Towards Data-centric Cold-start Recommendations

arXiv:2306.17256v4 Announce Type: replace-cross
Abstract: Recommendation systems help users find information that matches their interests based on their historical behaviors. However, generating personalized recommendations becomes challenging in the absence of historical user-item interactions, a practical problem for startups known as the system cold-start recommendation. Current research tackles user or item cold-start scenarios but lacks solutions for system cold-start. To tackle the problem, we initially propose PromptRec, a simple but effective approach based on in-context learning of language models, where we …

arxiv cs.ai cs.cl cs.ir cs.si data data-centric language language models recommendations recommenders serve small small language models type