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Author

Fahmida Islam

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Open access 2026

Federated Learning With Noisy and Imbalanced Data: A Contrastive Reliability-Based Framework for Long-Tail-Aware Client Selection

ConTaFL is introduced, a contrastive and tail-aware FL client selection framework that systematically addresses the aforementioned key challenges through coordinated mechanisms and consistently outperforms state-of-the-art FL frameworks across diverse noisy and non-IID settings while improving global model robustness a...

Fahmida Islam, Adnan Mahmood, Ying-Xun Wang et al. · 0 citations
Conference Open access Jul 2026

When Confidence Fails: Overconfidence in LLMS Under Uncertainty and Missing Clinical Information

An evaluation framework based on the MedMCQA dataset consisting of two complementary uncertainty settings is proposed, which introduces linguistic uncertainty cues through prompt modifications to simulate ambiguous clinical contexts and observes significant variation across models in their ability to abstain when the c...

Maryam Tahermazandarani, Adnan Mahmood, Fahmida Islam et al. · 0 citations

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