Latest Articles for Data Augmentation

This study improves GNN performance through effective graph explanations.

A new approach to integrate diverse cultural insights into language models.

Understanding how to build more reliable machine learning systems against adversarial threats.

A new framework enhances conversational search by improving diverse data generation.

Enhancing text-to-SQL models by integrating diverse question phrasing.

This article explores how data augmentation improves learning in deep reinforcement learning.

Study shows audio augmentation can enhance speech recognition in low-resource languages.

Investigating deepfake audio to enhance transcription models for less common languages.

Hyperedge Augmentation enhances GNNs by capturing complex relationships in data.

This article explores how comment generation improves large language models’ coding abilities.

This paper discusses challenges and solutions in visual reinforcement learning performance.

Enhancing computer understanding of images and text through advanced training techniques.

Exploring data augmentation techniques and their impact on NLP models.

A new method helps robots learn tasks using simulated data.

Exploring the role of ChatGPT in monitoring medication safety through event extraction.

MOVE integrates biological data to enhance cancer research and treatment strategies.

A new method enhances machine learning of audio-visual data.

A new approach enhances detection of subtle cyber threats using advanced data methods.

A new method enhances sound recognition and source location without labels.

This article discusses enhancing predictions using fractal interpolation in machine learning models.

Exploring advancements in automated audio captioning and its impact on accessibility.

A look at RAG and fine-tuning methods for enhancing LLMs' performance on rare topics.

Auxiliary Fourier-basis Augmentation enhances image robustness in computer vision models.

Examining how data augmentation techniques affect model performance across different classes.

MolNexTR improves recognition of chemical structures from images with advanced techniques.

New techniques improve segmentation accuracy in chest radiographs.

This research examines spectral imbalance to enhance fairness in machine learning classification models.

Learn how projection heads improve machine learning models.

This study investigates the role of synthetic examples in authorship verification.

Examining the role of data augmentation versus contrastive learning in recommendations.

Innovative methods enhance time series analysis through automation and machine learning.

TransformMix improves data augmentation by preserving essential features in mixed images.

New methods enhance music score reading and interpretation.

A new approach to reduce bias in AI models and improve predictions.

A new method enhances data usage for better model performance.

New dataset aims to improve CAD diagnosis accuracy.

A method to enhance how machines interpret complex chart questions.

Using symmetry for better robot learning and performance in real-world tasks.

Efforts to enhance sentence embeddings for better handling of informal language.

Research focuses on enhancing user satisfaction models with balanced datasets.