Papers by Nicole Ren

1 papers
SLENDER: Structured Outputs for SLM-based NER in Low-Resource Englishes (2025.acl-industry)

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Challenge: Named Entity Recognition (NER) for low-resource variants of English remains challenging, as most models are trained on datasets predominantly focused on American or British English.
Approach: They propose a new output format for Named Entity Recognition (NER) that achieves a three-fold reduction in inference time compared to JSON format.
Outcome: The proposed output format achieves a three-fold reduction in inference time on average compared to JSON format, which is widely used for structured outputs.

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