Author

Nazreen Shah

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#artificial intelligence Preprint Aug 2026

Partition-Aware Unlearning for Removing Spurious Correlations in Large Vision-Language Models

The results show that PURGE consistently reduces hallucinations and spurious-correlation-driven errors while maintaining or improving overall performance in most evaluated settings, providing both a reusable evaluation protocol and an effective mitigation framework for more reliable LVLMs.

Aditi Sarker, Nazreen Shah, Rafi Ibn Sultan et al. · 0 citations

Preprint Aug 2026

Federated Continual Learning as a Distributed Drift-Plus-Penalty Control Problem

This work casts FCL as a stochastic control problem and proposes Federated Queue-regulated Continual Learning (FedQCL), a framework based on Lyapunov drift-plus-penalty (DPP) optimization that outperforms state-of-the-art baselines with respect to accuracy while significantly reducing forgetting under heterogeneous data distributions.

Nazreen Shah, Naveen Kumar, Reddy Somireddy et al. · 0 citations