Papers by Seungjoon Lee

    1 papers
    Comparison-based Active Preference Learning for Multi-dimensional Personalization (2025.acl-long)

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    Challenge: Large language models have shown remarkable success, but aligning them with human preferences remains a core challenge.
    Approach: They propose to capture implicit user preferences from comparative feedback to improve model performance.
    Outcome: The proposed framework is able to capture implicit user preferences from comparative feedback.

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