Latest Articles for Data Science

Improving computer programs for solving math word problems through better data examples.

KGExplainer enhances transparency in knowledge graph completion through meaningful explanations.

Exploring the viability of smaller language models for effective robotic task planning.

Learn about conditional optimal transport and its applications in data transformation.

Structurally Flexible Neural Networks improve adaptability for diverse tasks.

A method to improve language model performance across diverse languages during compression.

A new approach to reduce CNN complexity while maintaining performance.

New algorithms ensure fairness and diversity in data selection.

A framework for improving model performance in changing conditions.

A new method improves image analysis in digital pathology.

Examining strategies to improve language model performance across different languages.

This article discusses the Majority-of-Three algorithm for improving learning accuracy.

Research focuses on improving neural network verification with minimal NAP specifications.

Xenovert helps machine learning models adjust to changes in data without retraining.

Learn how to adapt models for different data sets effectively.

New tensor methods simplify high-dimensional data for better analysis.

This approach improves segmentation of medical images without extensive labeled data.

Introducing Smart, a method for better GNN performance in changing graphs.

New techniques enhance language models for finance using Adaptive Semantic Space Learning.

A clear guide for designing high-quality simulations in data science research.

Research enhances robotic pruning accuracy using simulation and deep learning techniques.

Exploring the need for clarity in AI decision-making processes.

A new method accelerates merge tree comparisons in scientific data analysis.

This research reveals task vectors that enhance visual model performance without extra examples.

A new method enhances active learning for imbalanced datasets.

This study focuses on refining smaller language models for South Slavic languages.

Analyzing the relationship between contrastive learning and traditional methods like PCA.

Exploring the connection between neural networks and cellular automata through many-valued logic.

Research aims to make language models safer and more useful for users.

New method improves model performance amidst label noise.

Exploring the security challenges posed by self-supervised learning and no-label backdoor attacks.

Learning hidden factors from incomplete data in complex systems.

Discover how quantum frequential computers are changing technology with speed and efficiency.

Learn how recommendation systems influence user preferences using multi-armed bandit algorithms.

Examining gradient descent in phase retrieval and its optimization challenges.

This library offers an efficient way to calculate molecular fingerprints for chemists.

A new dataset improves computer recognition of objects in different states.

Exploring diversity and bias in healthcare data research and its impact.

A new method improves training data for offline reinforcement learning.

This study introduces NNBF to enhance ground state calculations in quantum chemistry.