Latest Articles for Robustness

This article examines how relational concepts shape knowledge retrieval in large language models.

Researchers develop new methods for training robots safely in risky environments.

A study on how pose estimation models perform with corrupted images.

Ensuring AI explanations are clear and reliable for user trust.

A new method for estimating edge density in random graphs while ensuring privacy.

Research highlights safety neurons' role in enhancing LLM safety and responsibility.

An overview of partially hyperbolic systems and their complex behaviors.

Data balancing is crucial for fairness and accuracy in machine learning models.

A new method helps identify weak points in deep learning models quickly.

A method to enhance system efficiency without detailed knowledge.

An in-depth look at how language models maintain accuracy with structural changes.

Analyzing how noise influences the efficiency of transport systems.

Explore the working and applications of diffusion models in generative AI.

Introducing a new method for better solutions in complex engineering and robotics tasks.

Examining risks and defenses against backdoor attacks in AI models.

Exploring backdoor attacks and graph reduction methods in GNNs.

A new method enhances video data management for better understanding and efficiency.

This research examines how visual issues impact Visual Question Answering models.

This method helps clarify complex, changing data by reducing noise while retaining important features.

LayerShuffle enhances the robustness of neural networks by enabling flexible layer execution.

Learn how bifiltrations enhance data analysis by examining two parameters simultaneously.

A new framework aims to improve accuracy in power system security evaluations.

New methods enhance control system performance amidst uncertainties.

Improving trust and compliance in language models through accurate source attribution.

Examining how training influences model performance in adversarial situations.

A new approach to improve efficiency in pattern recognition tasks.

A new benchmark addresses the need for standard evaluation in spatio-temporal prediction.

Examining adversarial attacks and model robustness in semantic segmentation.

This article reviews the reliability of models in analyzing visual data.

This article compares different ingestible antenna types for health monitoring in the GI tract.

Elliptical Attention improves focus and performance in AI tasks.

SafePowerGraph enhances GNN performance in power grid operations prioritizing safety.

Research shows how variability enhances ANN controllers for better performance in diverse environments.

A new model enhances trajectory prediction for self-driving cars in diverse conditions.

Examining the role of robustness in estimating unknown distributions from samples.

A method to improve language model behavior against harmful outputs.

A study on improving CNNs using partial labels and adversarial attack models.

Examining AI decision-making and its unexpected challenges.

VeriQR improves robustness in quantum machine learning models against noise.

A new approach to assess the reliability of methods explaining AI decision-making.