Antoine Doucet | DeepAI

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∙ 03/30/2023

Yes but.. Can ChatGPT Identify Entities in Historical Documents?

Large language models (LLMs) have been leveraged for several years now, ...

0 Carlos-Emiliano González-Gallardo, et al. ∙

∙ 01/31/2023

Archive TimeLine Summarization (ATLS): Conceptual Framework for Timeline Generation over Historical Document Collections

Archive collections are nowadays mostly available through search engines...

0 Nicolas Gutehrlé, et al. ∙

∙ 01/20/2023

Contextualizing Emerging Trends in Financial News Articles

Identifying and exploring emerging trends in the news is becoming more e...

0 Nhu Khoa Nguyen, et al. ∙

∙ 01/17/2023

The Recent Advances in Automatic Term Extraction: A survey

Automatic term extraction (ATE) is a Natural Language Processing (NLP) t...

0 Hanh Thi Hong Tran, et al. ∙

∙ 12/12/2022

Ensembling Transformers for Cross-domain Automatic Term Extraction

Automatic term extraction plays an essential role in domain language und...

0 Hanh Thi Hong Tran, et al. ∙

∙ 07/04/2022

Using contextual sentence analysis models to recognize ESG concepts

This paper summarizes the joint participation of the Trading Central Lab...

0 Elvys Linhares Pontes, et al. ∙

∙ 12/15/2021

Named entity recognition architecture combining contextual and global features

Named entity recognition (NER) is an information extraction technique th...

0 Tran Thi Hong Hanh, et al. ∙

∙ 09/23/2021

Named Entity Recognition and Classification on Historical Documents: A Survey

After decades of massive digitisation, an unprecedented amount of histor...

0 Maud Ehrmann, et al. ∙

∙ 04/14/2021

Event Detection as Question Answering with Entity Information

In this paper, we propose a recent and under-researched paradigm for the...

0 Emanuela Boros, et al. ∙

∙ 04/13/2021

Transformer-based Methods for Recognizing Ultra Fine-grained Entities (RUFES)

This paper summarizes the participation of the Laboratoire Informatique,...

0 Emanuela Boros, et al. ∙

∙ 03/05/2020

AI outperformed every dermatologist: Improved dermoscopic melanoma diagnosis through customizing batch logic and loss function in an optimized Deep CNN architecture

Melanoma, one of most dangerous types of skin cancer, re-sults in a very...

0 Cong Tri Pham, et al. ∙

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