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NER

The named entity recognition (NER) involves identification of key information in the text and classification into a set of predefined categories. This includes standard entities in the text like Part of Speech (PoS) and entities like places, names etc...

Papers

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Showing 361–370 of 1729 papers

TitleStatusHype
Reading Order Matters: Information Extraction from Visually-rich Documents by Token Path PredictionCode1
One For All & All For One: Bypassing Hyperparameter Tuning with Model Averaging For Cross-Lingual TransferCode0
Learning to Rank Context for Named Entity Recognition Using a Synthetic DatasetCode0
Empirical Study of Zero-Shot NER with ChatGPTCode1
Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related FeaturesCode0
PuoBERTa: Training and evaluation of a curated language model for SetswanaCode0
To token or not to token: A Comparative Study of Text Representations for Cross-Lingual TransferCode0
MProto: Multi-Prototype Network with Denoised Optimal Transport for Distantly Supervised Named Entity RecognitionCode0
FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets—0
ProtoNER: Few shot Incremental Learning for Named Entity Recognition using Prototypical Networks—0
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