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2025 ICML ICML 2025

FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing

Authors

Fan Nie, Xiaotian Hou, Shuhang Lin, James Zou, Huaxiu Yao, Linjun Zhang

Topics

Artificial Intelligence > Core AI > Responsible AI Natural Language Processing > Applications > Question Answering Artificial Intelligence > Core AI > Large Language Models

Keywords

hypothesis testing type i error hallucinations factuality distribution-free human-annotated samples
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