15 citations · 35 across the 27 of their papers we have counts for
3 papers · 1 filter
Mixed-Precision Quantization for Language Models: Techniques and Prospects
Mariam Rakka, Marios Fournarakis, Olga Krestinskaya +5
The rapid scaling of language models (LMs) has resulted in unprecedented computational, memory, and energy requirements, making their training and deployment increasingly unsustain…
CIMNAS: A Joint Framework for Compute-In-Memory-Aware Neural Architecture Search
Olga Krestinskaya, Mohammed E. Fouda, Ahmed Eltawil +1
To maximize hardware efficiency and performance accuracy in Compute-In-Memory (CIM)-based neural network accelerators for Artificial Intelligence (AI) applications, co-optimizing b…
On Jailbreaking Quantized Language Models Through Fault Injection Attacks
Noureldin Zahran, Ahmad Tahmasivand, Ihsen Alouani +2
The safety alignment of Language Models (LMs) is a critical concern, yet their integrity can be challenged by direct parameter manipulation attacks, such as those potentially induc…