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洞察 - Sequential Recommendation with LLMs
GOT4Rec: Using "Graph of Thoughts" and LLMs for Improved Sequential Recommendations
GOT4Rec leverages the "Graph of Thoughts" (GoT) prompting strategy within Large Language Models (LLMs) to significantly improve sequential recommendation accuracy by effectively capturing and integrating short-term, long-term, and collaborative user preferences.
Dynamic Adaptation of Large Language Models for Enhanced Sequential Recommendation by Incorporating Intra-Item and Collaborative Knowledge
The paper introduces DARec, a novel sequential recommendation model that leverages the power of large language models (LLMs) while addressing their limitations in capturing intra-item relations and long-term collaborative knowledge.
