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20192026
most citedIntegrating Dictionary Feature into A Deep Learning Model for Disease Named Entity Recognition

3 citations · 3 across the 5 of their papers we have counts for

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6 papers · 1 filter

cs.CL2026

Transformer-Based Model for Multilingual Hope Speech Detection

Nsrin Ashraf, Mariam Labib, Hamada Nayel

This paper describes a system that has been submitted to the "PolyHope-M" at RANLP2025. In this work various transformers have been implemented and evaluated for hope speech detect…

cs.CL2026

CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data

Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett +94

Language identification (LID) is a fundamental step in curating multilingual corpora. However, LID models still perform poorly for many languages, especially on the noisy and heter…

cs.CL2022

BFCAI at SemEval-2022 Task 6: Multi-Layer Perceptron for Sarcasm Detection in Arabic Texts

Nsrin Ashraf, Fathy Elkazaz, Mohamed Taha +2

This paper describes the systems submitted to iSarcasm shared task. The aim of iSarcasm is to identify the sarcastic contents in Arabic and English text. Our team participated in i…

cs.CL2020

NAYEL at SemEval-2020 Task 12: TF/IDF-Based Approach for Automatic Offensive Language Detection in Arabic Tweets

Hamada A. Nayel

In this paper, we present the system submitted to "SemEval-2020 Task 12". The proposed system aims at automatically identify the Offensive Language in Arabic Tweets. A machine lear…

cs.CL20193 cited

Integrating Dictionary Feature into A Deep Learning Model for Disease Named Entity Recognition

Hamada A. Nayel, Shashrekha H. L

In recent years, Deep Learning (DL) models are becoming important due to their demonstrated success at overcoming complex learning problems. DL models have been applied effectively…

cs.CL2019

Improving Multi-Word Entity Recognition for Biomedical Texts

Hamada A. Nayel, H. L. Shashirekha, Hiroyuki Shindo +1

Biomedical Named Entity Recognition (BioNER) is a crucial step for analyzing Biomedical texts, which aims at extracting biomedical named entities from a given text. Different super…