Papers by James Hensman

1 papers
Learning to Extract Structured Entities Using Language Models (2024.emnlp-main)

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Challenge: Language Models (LMs) play a pivotal role in extracting structured information from unstructured text.
Approach: They propose to reformulate the task to be entity-centric, enabling the use of diverse metrics that can provide more insights from various perspectives.
Outcome: The proposed model outperforms baselines and human evaluations on the extracted entities.

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