12 citations · 40 across the 7 of their papers we have counts for
7 papers
mucAI at BAREC Shared Task 2025: Towards Uncertainty Aware Arabic Readability Assessment
Ahmed Abdou
We present a simple, model-agnostic post-processing technique for fine-grained Arabic readability classification in the BAREC 2025 Shared Task (19 ordinal levels). Our method appli…
mucAI at WojoodNER 2024: Arabic Named Entity Recognition with Nearest Neighbor Search
Ahmed Abdou, Tasneem Mohsen
Named Entity Recognition (NER) is a task in Natural Language Processing (NLP) that aims to identify and classify entities in text into predefined categories. However, when applied…
Mind Your Neighbours: Leveraging Analogous Instances for Rhetorical Role Labeling for Legal Documents
T. Y. S. S Santosh, Hassan Sarwat, Ahmed Abdou +1
Rhetorical Role Labeling (RRL) of legal judgments is essential for various tasks, such as case summarization, semantic search and argument mining. However, it presents challenges s…
Gaze-enhanced Crossmodal Embeddings for Emotion Recognition
Ahmed Abdou, Ekta Sood, Philipp Müller +1
Emotional expressions are inherently multimodal -- integrating facial behavior, speech, and gaze -- but their automatic recognition is often limited to a single modality, e.g. spee…
HoneyModels: Machine Learning Honeypots
Ahmed Abdou, Ryan Sheatsley, Yohan Beugin +2
Machine Learning is becoming a pivotal aspect of many systems today, offering newfound performance on classification and prediction tasks, but this rapid integration also comes wit…
Enhancing Gradient-based Attacks with Symbolic Intervals
Shiqi Wang, Yizheng Chen, Ahmed Abdou +1
Recent breakthroughs in defenses against adversarial examples, like adversarial training, make the neural networks robust against various classes of attackers (e.g., first-order gr…
MixTrain: Scalable Training of Verifiably Robust Neural Networks
Shiqi Wang, Yizheng Chen, Ahmed Abdou +1
Making neural networks robust against adversarial inputs has resulted in an arms race between new defenses and attacks. The most promising defenses, adversarially robust training a…