Papers by Karen Pinel-Sauvagnat

2 papers
Not all Hallucinations are Good to Throw Away When it Comes to Legal Abstractive Summarization (2025.naacl-long)

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Challenge: Existing models for summarization of legal documents rely on external knowledge to generate abstracts.
Approach: They propose an entity-driven approach that learns the model to generate factual hallucinations . they evaluate legal documents in English and French to evaluate their results .
Outcome: The proposed approach reduces non-factual hallucinations and maximizes summary coverage and factual hallucines at entity-level.
Exploring the Value of Multi-View Learning for Session-Aware Query Representation (2022.findings-naacl)

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Challenge: Existing approaches to learn distributed query representations only consider user’s query reformulations or system’s rankings . previous studies show that user’ s query behavior and knowledge change depending on the system’ 'results' and intertwine and affect each other during the completion of a search task.
Approach: They propose to use multi-view learning methods to align query embeddings with document ranking representations using transformers.
Outcome: The proposed approach can capture search intent semantics and can reflect user's query behavior and knowledge.

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