Papers by Bingjing Xu

1 papers
ICL-Bandit: Relevance Labeling in Advertisement Recommendation Systems via LLM (2025.findings-emnlp)

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Challenge: In-context learning (ICL) is a common practice to enhance LLM performance on domain-specific tasks.
Approach: They propose a method that leverages large language models to enhance query-ad relevance labeling . they identify and provide superior demonstrations for ICL, thereby improving labeling performance .
Outcome: The proposed method improves query-ad relevance labeling performance by providing demonstrations.

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