Latest Articles for Faithfulness

Introducing PACE, a structured approach for trustworthy AI explanations.

Examining the impact of model size on data-to-text generation performance.

Meta-Rank offers a more consistent way to evaluate AI attribution methods.

A new tool for assessing explainability methods in AI systems.

Examining the issues and advancements in cross-lingual summarization methods.

This project examines how AI interprets clinical trial reports and identifies truthful statements.

A new approach to enhance transparency in AI responses and decision-making.

LATEC offers a robust evaluation of XAI methods for better AI transparency.

A look into assessing the trustworthiness of AI explanations through adversarial sensitivity.

A new method enhances accuracy and clarity in diagram creation from academic texts.

Exploring how fine-tuning affects reasoning in language models.

Discover how smart systems are changing the way we handle documents.

Discover how curriculum learning tackles noisy data in text generation.