Papers with determinantal point process

2 papers
RELexED: Retrieval-Enhanced Legal Summarization with Exemplar Diversity (2025.findings-naacl)

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Challenge: Current approaches to legal summarization struggle with content theme deviation and inconsistent writing styles due to the content of the source document.
Approach: They propose a retrieval-augmented framework that utilizes exemplar summaries along with the source document to guide the model.
Outcome: The proposed model outperforms models that do not utilize exemplars and those that rely on similarity-based exemplar selection.
Correlation-Aware Example Selection for In-Context Learning with Nonsymmetric Determinantal Point Processes (2025.emnlp-main)

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Challenge: Existing studies on in-context learning (ICL) focus on the selection of individual examples and ignore correlations among examples.
Approach: They propose a method to capture positive and negative correlations using the determinantal point process . they optimize the method via kernel decomposition-based MLE to fit a constructed pseudo-labeled dataset .
Outcome: The proposed method outperforms baselines in ICL example selection.

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