Latest Articles for Explanations

A new method enhances trust and decision-making for AI-assisted advice.

LinkLogic provides clarity and reliability for link prediction in knowledge graphs.

A new method enhances the transparency of knowledge graph embedding models.

Research examines the link between AI explanations and user trust.

A new method improves confidence scoring in language models using stable explanations.

HOGE enhances explanations of Graph Neural Networks using cell complexes.

PredEx offers predictions and explanations for legal judgments in India.

New method evaluates the trustworthiness of ML predictions automatically.

A new method uses natural language explanations to improve entity matching.

This study presents an innovative method for generating trustworthy explanations in automated medical coding.

A clear framework to assess understanding in AI systems.

A tool measures how helpful AI explanations are for decision-making.

Exploring the need for clear explanations in Graph Neural Networks.

A new model enhances translation quality by explaining and correcting errors.

This study examines how explanations impact user perceptions of AI capabilities.

A new method enhances reasoning skills of language models through question analysis.

A new classifier improves explainability and accuracy in AI image recognition.

This study explores how emotions from news headlines can be interpreted through personal explanations.

A new approach to explain MCTS clearly for non-technical users.

A new framework for verifying authorship with clear explanations.

Exploring the need for semantic continuity in AI systems for better understanding.

A new method enhances clarity in image recognition tasks.

AIDE customizes explanations for machine learning predictions based on user intent.

A new method enhances understanding of 3D segmentation models in healthcare.

Examining how Shapley value aids in data interpretation and query results.

A new approach offers clearer explanations for image classification decisions.

A novel approach to enhance understanding of GNN predictions through causal relationships.

This article explores how paraconsistent logic improves abductive reasoning in complex situations.

Exploring how external inputs shape responses of large language models.

This study examines the reliability of rationalization models under adversarial attacks.

Examining how explanation styles impact user understanding and trust in AI tools.

A new model improves depression detection in social media posts with clear explanations.

Examining LVLMs' effectiveness in generating multilingual art explanations.

A novel method enhances detection and explanation of fake news.

Examining how explanation errors affect trust in autonomous vehicles.

AI explanations can aid learning but lack lasting impact.

Exploring how clearer explanations enhance trust in recommendations.

A new method improves AI explanations through collaboration between two language models.

A new method interprets authorship attribution models for improved accuracy and trust.

This article explores how context improves user decision-making with AI systems.