Large language models for generative information extraction: A survey
Information extraction (IE) aims to extract structural knowledge (such as entities, relations,
and events) from plain natural language texts. Recently, generative Large Language Models …
and events) from plain natural language texts. Recently, generative Large Language Models …
Gliner: Generalist model for named entity recognition using bidirectional transformer
Named Entity Recognition (NER) is essential in various Natural Language Processing (NLP)
applications. Traditional NER models are effective but limited to a set of predefined entity …
applications. Traditional NER models are effective but limited to a set of predefined entity …
Rethinking Negative Instances for Generative Named Entity Recognition
Y Ding, J Li, P Wang, Z Tang, B Yan… - arXiv preprint arXiv …, 2024 - arxiv.org
Large Language Models (LLMs) have demonstrated impressive capabilities for generalizing
in unseen tasks. In the Named Entity Recognition (NER) task, recent advancements have …
in unseen tasks. In the Named Entity Recognition (NER) task, recent advancements have …
Diluie: constructing diverse demonstrations of in-context learning with large language model for unified information extraction
Q Guo, Y Guo, J Zhao - Neural Computing and Applications, 2024 - Springer
Large language models (LLMs) have demonstrated promising in-context learning
capabilities, especially with instructive prompts. However, recent studies have shown that …
capabilities, especially with instructive prompts. However, recent studies have shown that …
A Systematic Literature Review on Custom NER with Evidence-Based Software Engineering
As the significance of data continues to grows, so does the importance of data analysis
methods. Various models are currently being applied, and new models are being proposed …
methods. Various models are currently being applied, and new models are being proposed …
Efficient Multi-Class Object Re-Identification Approach with A Unified Model
QH Che, GN Tran - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
Re-identification (ReID) is a critical field in com-puter vision. In previous studies, ReID
models have primarily focused on identifying specific objects, such as persons or vehi-cles …
models have primarily focused on identifying specific objects, such as persons or vehi-cles …
[PDF][PDF] Lightweight Traffic Referring Expression Comprehension System Based on Sparse Cross-Modal Attention and Multi-Modal Joint Augmentation
CM Attention - researchgate.net
In many instances, traffic supervisors, drivers, or autonomous driving systems need to
search for and pinpoint specific traffic targets. Relying on human visual location is …
search for and pinpoint specific traffic targets. Relying on human visual location is …