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Zero-shot Named Entity Recognition (NER)

Named Entity Recognition is Zero-shot Settings. The model has not been trained in the specific dataset

Papers

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Showing 1–11 of 11 papers

TitleStatusHype
Cross-Lingual IPA Contrastive Learning for Zero-Shot NER—0
A Cooperative Multi-Agent Framework for Zero-Shot Named Entity RecognitionCode0
Familiarity: Better Evaluation of Zero-Shot Named Entity Recognition by Quantifying Label Shifts in Synthetic Training DataCode1
ReverseNER: A Self-Generated Example-Driven Framework for Zero-Shot Named Entity Recognition with Large Language Models—0
SandboxAQ's submission to MRL 2024 Shared Task on Multi-lingual Multi-task Information Retrieval—0
Rethinking Negative Instances for Generative Named Entity RecognitionCode2
NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated DataCode1
GoLLIE: Annotation Guidelines improve Zero-Shot Information-ExtractionCode2
PromptNER: Prompting For Named Entity Recognition—0
InstructUIE: Multi-task Instruction Tuning for Unified Information ExtractionCode2
Textual Entailment for Event Argument Extraction: Zero- and Few-Shot with Multi-Source LearningCode0
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