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SmartSpanNER: Making SpanNER Robust in Low Resource Scenarios (2023.findings-emnlp)

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Challenge: Named Entity Recognition (NER) is one of the most fundamental tasks in natural language processing.
Approach: They propose a method which introduces a Named Entity Head (NEH) prediction task to SpanNER and performs multi-task learning together with task of span classification.
Outcome: The proposed method improves the robustness of SpanNER in low resource scenarios on the CoNLL03, Few-NERD, GENIA and ACE05 benchmark datasets.

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