20 citations · 22 across the 4 of their papers we have counts for
4 papers
Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM
Noor Khalal, Abdallah Alaa-Eddine Djamai, Imed Keraghel +1
In Natural Language Processing (NLP), dealing with underrepresented topics is challenging, especially in unsupervised tasks where clustering might not adequately capture minority t…
When Labels Are Scarce: A Systematic Mapping of Label-Efficient Code Vulnerability Detection
Noor Khalal, Chakib Fettal, Lazhar Labiod +1
Machine-learning-based code vulnerability detection (CVD) has progressed rapidly, from deep program representations to pretrained code models and LLM-centered pipelines. Yet depend…
Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering
Imed Keraghel, Mohamed Nadif
Recent advances in machine learning, particularly Large Language Models (LLMs) such as BERT and GPT, provide rich contextual embeddings that improve text representation. However, c…
Recent Advances in Named Entity Recognition: A Comprehensive Survey and Comparative Study
Imed Keraghel, Stanislas Morbieu, Mohamed Nadif
Named Entity Recognition seeks to extract substrings within a text that name real-world objects and to determine their type (for example, whether they refer to persons or organizat…