MultiCoNER: A large-scale multilingual dataset for complex named entity recognition
We present MultiCoNER, a large multilingual dataset for Named Entity Recognition that
covers 3 domains (Wiki sentences, questions, and search queries) across 11 languages, as …
covers 3 domains (Wiki sentences, questions, and search queries) across 11 languages, as …
Multiconer v2: a large multilingual dataset for fine-grained and noisy named entity recognition
We present MULTICONER V2, a dataset for fine-grained Named Entity Recognition covering
33 entity classes across 12 languages, in both monolingual and multilingual settings. This …
33 entity classes across 12 languages, in both monolingual and multilingual settings. This …
Task relation distillation and prototypical pseudo label for incremental named entity recognition
Incremental Named Entity Recognition (INER) involves the sequential learning of new entity
types without accessing the training data of previously learned types. However, INER faces …
types without accessing the training data of previously learned types. However, INER faces …
Decomposing logits distillation for incremental named entity recognition
Incremental Named Entity Recognition (INER) aims to continually train a model with new
data, recognizing emerging entity types without forgetting previously learned ones. Prior …
data, recognizing emerging entity types without forgetting previously learned ones. Prior …
USTC-NELSLIP at SemEval-2022 task 11: Gazetteer-adapted integration network for multilingual complex named entity recognition
This paper describes the system developed by the USTC-NELSLIP team for SemEval-2022
Task 11 Multilingual Complex Named Entity Recognition (MultiCoNER). We propose a …
Task 11 Multilingual Complex Named Entity Recognition (MultiCoNER). We propose a …
Dynamic gazetteer integration in multilingual models for cross-lingual and cross-domain named entity recognition
Named entity recognition (NER) in a real-world setting remains challenging and is impacted
by factors like text genre, corpus quality, and data availability. NER models trained on …
by factors like text genre, corpus quality, and data availability. NER models trained on …
Decoupled Hyperbolic Graph Attention Network for Cross-domain Named Entity Recognition
J Xu, Y Cai - Proceedings of the 46th International ACM SIGIR …, 2023 - dl.acm.org
To address the scarcity of massive labeled data, cross-domain named entity recognition
(cross-domain NER) attracts increasing attention. Recent studies focus on decomposing …
(cross-domain NER) attracts increasing attention. Recent studies focus on decomposing …
ITA: Image-text alignments for multi-modal named entity recognition
Recently, Multi-modal Named Entity Recognition (MNER) has attracted a lot of attention.
Most of the work utilizes image information through region-level visual representations …
Most of the work utilizes image information through region-level visual representations …
Exploring modular task decomposition in cross-domain named entity recognition
Cross-domain Named Entity Recognition (NER) aims to transfer knowledge from the source
domain to the target, alleviating expensive labeling costs in the target domain. Most prior …
domain to the target, alleviating expensive labeling costs in the target domain. Most prior …
Linkner: Linking local named entity recognition models to large language models using uncertainty
Named Entity Recognition (NER) serves as a fundamental task in natural language
understanding, bearing direct implications for web content analysis, search engines, and …
understanding, bearing direct implications for web content analysis, search engines, and …