Filtering LLM-Synthesized Data for Cold-Start Recommendation: A Progressive Influence Function Approach
Leveraging Large Language Models (LLMs)-synthesized data to enable representation learning for cold-start entities has emerged as a promising solution for addressing cold-start recommendations. However, existing studies often over-rely on LLM-generated data while neglecting the detrimental noise it may introduce. This...