7 accepted papers
The rapid growth of large language models (LLMs) has heightened the importance of post-training quantization (PTQ) for reducing memory and computation costs. Among PTQ methods, GPTQ has gained significant attention for its efficiency, enabling billion-scale LLMs to be quantized within a few GPU hour…
Post-training quantization (PTQ) is a promising solution for deploying large language models (LLMs) on resource-constrained devices. Early methods developed for small-scale networks, such as ResNet, rely on gradient-based optimization, which becomes impractical for hyper-scale LLMs with billions of…
With the increasing complexity of generative AI models, post-training quantization (PTQ) has emerged as a promising solution for deploying hyper-scale models on edge devices such as mobile and TVs. Existing PTQ schemes, however, consume considerable time and resources, which could be a bottleneck in…
Efficient inference has become crucial for hyper-scale AI models, including large language models, as their parameter count continues to increase for enhanced performance. This necessity holds true regardless of the computing environment, whether it be mobile devices or cloud servers. Quantization e…
This letter presents an automated sewing system designed for smart garment manufacturing, incorporating machine vision capabilities into a custom-built sewing machine. The vision system captures an image of the fabric pattern placed between two acrylic plates with a small opening, utilizing a deep l
Zero-shot quantization is a promising approach for developing lightweight deep neural networks when data is inaccessible owing to various reasons, including cost and issues related to privacy. By exploiting the learned parameters (u and sigma) of batch normalization layers in an FP32-pre-trained mod…
We propose a soft robotic gripper that can handle various types of fabrics with delicacy for applications in the field of garment manufacturing. The design was inspired by the adhesion mechanism of a parasitic fish called `lamprey'. The proposed gripper not only is able to pick up and hold a single