Latest Articles for Data Science

Introducing a novel approach to categorize and study emotions through the Emotion Frame Ontology.

Examining how deep neural networks learn and the challenges they face.

A new method ensures fairness in machine learning using incomplete causal information.

Discover how combining topics and time boosts recommendation accuracy.

Explore self-training's role in improving data-to-text processes.

Exploring the role of language models in materials science literature analysis.

Researchers propose new methods for managing unpredictable systems using data-driven techniques.

Orion-14B excels in understanding and generating multilingual text with 14 billion parameters.

A new approach enhances NLP models against adversarial attacks through targeted paraphrasing.

A deep dive into trustworthiness in AI and its importance.

Examining the complexities and strategies for neural network learning in various data types.

A look at algorithm auditing research and its societal impacts.

Examining how ML practitioners implement responsible machine learning practices and the challenges they face.

This article discusses using deep learning to estimate the Hurst parameter in fractional processes.

NECHO improves health issue predictions using a unique data integration method.

A look into spectral algorithms and their role in machine learning predictions.

This study focuses on the role of glutathione in cancer and its transport mechanisms.

A new framework improves recommendation systems through a scalable knowledge base.

A method to enhance learning for underrepresented data classes using head class information.

New methods improve accuracy and efficiency in predicting network connections.

A new system improves schema matching accuracy using generative tags and advanced features.

This research enhances intrusion detection using machine learning techniques for better cybersecurity.

A new method for better understanding cause-and-effect relationships.

Introducing a flexible model for open-vocabulary semantic segmentation using language and visual features.

WARM aims to improve alignment of large language models with human values.

A new framework enhances GNNs to address oversmoothing issues effectively.

A method improves efficiency in training and using large language models.

Examining how LLMs prefer generated contexts over retrieved ones in answering questions.

A new framework enhances anomaly detection in graph data using active learning techniques.

Learn how cross-validation enhances the reliability of predictive models.

New techniques improve data generation in constrained environments using reflected diffusion models.

A new system enhances how robots gather and learn from real-world data.

Innovative methods to enhance task execution and reduce failures in crowdsourcing.

MORPH adapts malware detection systems to evolving threats with less manual input.

A new method improves feature selection efficiency in machine learning models.

Explore how interpretability illusions affect our view of neural networks.

A new deep learning model improves flight passenger traffic predictions for airlines.

This article discusses the need for clarity in machine learning models.

APT-Pipe automates prompt tuning for efficient text annotation using ChatGPT.

IICONGRAPH enhances the study of art by improving knowledge graphs.