4 papers
Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models
Rayyan Abdalla, Amir Hussein, Min Wu +1
Post-training quantization (PTQ) is critical for the efficient deployment of large language models (LLMs). Recent ultra-low-bit PTQ methods rely on rigid weight-saliency assumption…
Bi-VLM: Pushing Ultra-Low Precision Post-Training Quantization Boundaries in Vision-Language Models
Xijun Wang, Junyun Huang, Rayyan Abdalla +3
We address the critical gap between the computational demands of vision-language models and the possible ultra-low-bit weight precision (bitwidth bits) we can use for highe…
Analysis of Synchrosqueezed Transforms and Application Perspectives
Rayyan Abdalla
High-resolution time-frequency (TF) analysis plays crucial role in characterizing multicomponent signal (MCSs) and estimating oscillatory properties. Linear time-frequency represen…
Complex-valued Neural Networks -- Theory and Analysis
Rayyan Abdalla
Complex-valued neural networks (CVNNs) have recently been successful in various pioneering areas which involve wave-typed information and frequency-domain processing. This work add…