1 citations · 1 across the 5 of their papers we have counts for
7 papers
VisionMX: Unlocking Microscaling Post-Training Quantization for Vision Models
Elad Dror Cohen, Ofir Gordon, Lior Dikstein +2
Microscaling (MX) formats are emerging as a hardware-supported approach to efficient training and inference. They combine low-precision elements with shared block scales, but their…
PG-SELD: Physics-Guided Sound Event Localization and Detection
Elad Cohen, Elad Dror Cohen, Arnon Netzer +1
Sound event localization and detection (SELD) aims to jointly recognize sound events and estimate their directions of arrival from multichannel audio. Although recent deep learning…
Low-Latency State Space Voice Activity Detection with Robust Onset Time Evaluation
Elad Cohen, Arnon Netzer, Hai Victor Habi
Voice Activity Detection (VAD) systems are commonly evaluated using metrics such as the area under the receiver operating characteristic curve (AUROC), but these metrics do not acc…
MLoRQ: Bridging Low-Rank and Quantization for Transformer Compression
Ofir Gordon, Ariel Lapid, Elad Cohen +3
Deploying transformer-based neural networks on resource-constrained edge devices presents a significant challenge. This challenge is often addressed through various techniques, suc…
Efficient Image Restoration via Latent Consistency Flow Matching
Elad Cohen, Idan Achituve, Idit Diamant +2
Recent advances in generative image restoration (IR) have demonstrated impressive results. However, these methods are hindered by their substantial size and computational demands,…
EPTQ: Enhanced Post-Training Quantization via Hessian-guided Network-wise Optimization
Ofir Gordon, Elad Cohen, Hai Victor Habi +1
Quantization is a key method for deploying deep neural networks on edge devices with limited memory and computation resources. Recent improvements in Post-Training Quantization (PT…
HPTQ: Hardware-Friendly Post Training Quantization
Hai Victor Habi, Reuven Peretz, Elad Cohen +5
Neural network quantization enables the deployment of models on edge devices. An essential requirement for their hardware efficiency is that the quantizers are hardware-friendly: u…