Cross-Domain Named Entity Recognition

11 papers with code • 1 benchmarks • 1 datasets

This task has no description! Would you like to contribute one?


Most implemented papers

CrossNER: Evaluating Cross-Domain Named Entity Recognition

zliucr/CrossNER 8 Dec 2020

Cross-domain named entity recognition (NER) models are able to cope with the scarcity issue of NER samples in target domains.

Data Centric Domain Adaptation for Historical Text with OCR Errors

stefan-it/historic-domain-adaptation-icdar 2 Jul 2021

We propose new methods for in-domain and cross-domain Named Entity Recognition (NER) on historical data for Dutch and French.

Neural Adaptation Layers for Cross-domain Named Entity Recognition

yuchenlin/CDMA-NER EMNLP 2018

Recent research efforts have shown that neural architectures can be effective in conventional information extraction tasks such as named entity recognition, yielding state-of-the-art results on standard newswire datasets.

Cross-Domain NER using Cross-Domain Language Modeling

jiachenwestlake/Cross-Domain_NER ACL 2019

Due to limitation of labeled resources, cross-domain named entity recognition (NER) has been a challenging task.

Zero-Resource Cross-Domain Named Entity Recognition

Siddharthss500/zero-resource WS 2020

Existing models for cross-domain named entity recognition (NER) rely on numerous unlabeled corpus or labeled NER training data in target domains.

Coach: A Coarse-to-Fine Approach for Cross-domain Slot Filling

zliucr/coach ACL 2020

In this paper, we propose a Coarse-to-fine approach (Coach) for cross-domain slot filling.

Data Augmentation for Cross-Domain Named Entity Recognition

ritual-uh/style_ner EMNLP 2021

Current work in named entity recognition (NER) shows that data augmentation techniques can produce more robust models.

DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population

zjunlp/deepke 10 Jan 2022

We present an open-source and extensible knowledge extraction toolkit DeepKE, supporting complicated low-resource, document-level and multimodal scenarios in the knowledge base population.

FactMix: Using a Few Labeled In-domain Examples to Generalize to Cross-domain Named Entity Recognition

lifan-yuan/factmix COLING 2022

Few-shot Named Entity Recognition (NER) is imperative for entity tagging in limited resource domains and thus received proper attention in recent years.