factuality
Google DeepMind researchers introduce new benchmark to improve LLM factuality, reduce hallucinations
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Hallucinations, or factually inaccurate responses, continue to plague large language models (LLMs). Models falter particularly when they are given more complex tasks and when users are looking for specific and highly detailed responses. It’s a challenge…
FACTS Grounding: A new benchmark for evaluating the factuality of large language models
Responsibility & Safety Published 17 December 2024 Authors FACTS team Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and avoid hallucinations Large language models (LLMs) are transforming how we access information, yet their grip on factual accuracy remains imperfect. They can “hallucinate”…