It is shown that the usage of CRF weights in BERT-based architectures achieves noteworthy improvements in the overall NER task by approximately 12 %, and that in few-shot learning set-ups the effectiveness of CRF weights is much higher in smaller training sets.
With the rapid growth of digital text data, automatically extracting meaningful information from unstructured text has become essential for applications such as information retrieval, knowledge extraction, and question answering. Named Entity Recognition (NER) is a key task in Natural Language Processing (NLP) that ide...
Ilakkiya.B, Hemanandhini.I.G· 2026 4th International Confe...· 0 citations
A comprehensive natural language processing (NLP) pipeline for extracting key information and identifying industries, which outperforms traditional machine learning baselines and single deep learning models, offering more reliable recognition for minority classes.
Xin-Yi Xu· Applied and Computational En...· 0 citations
This paper proposes to use mBERT IndicBERT and XLM-RoBERTa language models pretrained on target and other related Indic language corpora and further fine-tune these models for the NER task.
P. M, H. G, S. N· International journal of res...· 0 citations
This study designs a unique, open-ended SIE task of extracting mutations in a given virus that modify its interaction with the host, and develops a new, multi-step retrieval augmented generation (RAG) framework called VILLA for SIE.
Blessy Antony, Amartya Dutta, Sneha Aggarwal et al.· Proceedings of the 32nd ACM...· 0 citations
An adaptive CNN architecture is introduced that shares most of the structure for multiple tasks including source detection, article illustration and geolocation of articles, and a new loss function based on Great Circle Distance is proposed for geolocation.
U.gayathri, M. Balaram· Journal of Science & Technol...· 0 citations
ReTaT is a dataset that can be used to train and evaluate systems for extracting relations whose expression spans the two modalities and its quality and suitability were assessed for the joint table-text relation extraction task using Large Language Models (LLMs).
Mohamed Ettaleb, Thibault Ehrhart, Nathalie Aussenac-Gilles et al.· International Conference on...· 1 citation
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