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cs.CR2026
TEE-X: TEE-aware Acceleration Framework for Large Vision Models at the Edge
Kurt M Wilson, Mohaiminul Al Nahian, Abeer Matar A. Almalky +5
Despite their remarkable success, machine learning models, particularly in vision applications, are alarmingly vulnerable to a range of security threats. One key factor in the atta…
cs.CR2025
COBRA: Catastrophic Bit-flip Reliability Analysis of State-Space Models
Sanjay Das, Swastik Bhattacharya, Shamik Kundu +3
State-space models (SSMs), exemplified by the Mamba architecture, have recently emerged as state-of-the-art sequence-modeling frameworks, offering linear-time scalability together…
cs.CR2024
GenBFA: An Evolutionary Optimization Approach to Bit-Flip Attacks on LLMs
Sanjay Das, Swastik Bhattacharya, Souvik Kundu +4
Large Language Models (LLMs) have revolutionized natural language processing (NLP), excelling in tasks like text generation and summarization. However, their increasing adoption in…