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Mahshid Rezakhani

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#machine learning Preprint Sep 2026

An Adversarial Zero-Shot Learning Approach for Anomaly Detection in Multivariate IoT Traffic Data

This paper proposes a novel framework for multivariate time-series anomaly detection that leverages adversarial learning and contrastive loss within a sequence-based Variational Autoencoder (VAE) architecture, and introduces encoder and decoder adaptor layers that align feature distributions across domains while preser...

Mahshid Rezakhani, Tolunay Seyfi, Fatemeh Afghah · 0 citations
#small language model Preprint Aug 2026

RTLGuard: A Lightweight Teacher-Student Defense for Poisoned RTL Code Generation Models

RTLGuard leverages a teacher-student framework designed to sanitize compromised RTL generation models by fine-tuning a small-scale,"clean"teacher model on a limited set of trusted RTL data, and incorporating feature alignment and knowledge distillation to suppress malicious behaviors.

Mahshid Rezakhani, K. Azar, H. Kamali · 0 citations

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