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T. Alyas

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Open access Oct 2026

A Deep Learning Framework for Evaluating and Mitigating Prompt Injection in LLM Agents

A deep learning-based approach to detecting and thwarting prompt injection attacks in LLM agent systems that uses a hybrid model of known and customer-generated adversarial prompts to combine transformer-based classification, semantic risk-scoring and adaptive mitigation procedures.

Najda Malik, Muhammad Hassan Ghulam Muhammad, T. Alyas et al. · 0 citations
#natural language process... Preprint Oct 2026

Neural POS Tagging for the Low-Resource Saraiki

The dataset, evaluation setup, and baseline results introduced in this work provide a benchmark for future research on Saraiki NLP and low-resource sequence labeling.

Usman Nawaz, Muhammad Junaid Iqbal, M. Asaf et al. · 0 citations
Open access Sep 2026

An Explainable and Computationally Efficient Machine Learning Framework for Breast Cancer Diagnosis Using Predictive and Interpretability Analysis

A systematic study of computational complexity has been conducted, and the results show that the training and inference latency of logistic regression is significantly lower than that of random forests, indicating its potential suitability for future resource-constrained clinical decision-support investigations after e...

A. ur Rehman, Mohamed A. Akela, T. Alyas et al. · 0 citations

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