Latest Articles for Quantization

BrightFit enhances course suggestions through a new two-stage retrieval approach.

Evaluating methods to enhance long context performance in language models.

Advancements in predicting speech quality using efficient methods for mobile devices.

A method to convert continuous data into a simpler, discrete form.

Combining pruning and quantization streamlines DNN efficiency for smaller devices.

Examining quantization techniques for better distributed learning across various network structures.

This article explores the benefits of using FP8 in federated learning.

Studying how quantization affects performance in different languages.

GPTQT enhances efficiency and performance in large language model quantization, making AI more accessible.

This paper presents a method to identify and manage harmful memes effectively.

ISQuant offers a new approach to quantization for efficient model deployment.

Evaluating quantization and pruning to optimize DRL models for limited resources.

A look into the safety concerns of compressed language models.

New method improves the performance of Binary Neural Networks under faults.

Study of Carrollian symmetries and their implications in modern physics.

Research focuses on the quantum behavior of ModMax, a modified electrodynamics model.

A new method enhancing model performance through effective outlier management.

New deep learning methods improve image compression efficiency and quality.

This study enhances qubit measurements using machine learning and FPGA technology.

Training DNNs on microcontrollers boosts efficiency and privacy in smart technology.

An overview of regular Lagrangians and their role in mathematics and physics.

This article examines how quantization can improve Transformer language model training efficiency.

MCU-MixQ enhances AI model performance on microcontrollers by optimizing resource use.

Study reveals improved sentiment analysis through local LLMs and majority voting.

Techniques for optimizing RNNs, focusing on Mamba and quantization challenges.

Smaller models tailored for specific fields, like medicine, show great potential.

New method enhances deep learning models for limited-resource devices.

An overview of MIDI music creation and its expressive potential.

Methods to speed up speaker diarization without sacrificing accuracy.

New methods aim to run powerful models on limited hardware efficiently.

Reducing model size and improving efficiency with lower precision formats.

Learn methods to optimize large language models for better performance and efficiency.

Utilizing LLMs to enhance e-commerce tasks through instruction tuning and quantization.

Examining how antenna numbers influence 1-bit MIMO communication performance.

Combining HW-NAS and ACO for efficient neural networks.

Exploring techniques to enhance LLM performance during inference.

A new method enhances efficiency and performance of multimodal large language models.

Learn how PQV-Mobile enhances ViTs for efficient mobile applications.

A look into the principles and challenges of string theory.

Research offers fresh views on black holes through a new quantization scheme.