Papers with dynamic interest adaptation

1 papers
Customizing In-context Learning for Dynamic Interest Adaption in LLM-based Recommendation (2025.findings-acl)

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Challenge: Existing Large Language Model (LLM)-based recommender systems face challenges to adapt to dynamic user interests without any model-level updates.
Approach: They propose a framework that establishes recommendation-oriented in-context learning by structuring recent user interactions and current inputs into ICL formats.
Outcome: The proposed model adapts to dynamic user interests without model updates without any model updates and is available online at https://anonymous.4open.science/r/RecICL-8003.

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