•1 min read•from Data Science
Benchmarking LLM Hallucinations
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At my company, we have initiated an internal project aimed at benchmarking large language models (LLMs) for hallucinations. Our goal is to develop both internal tools and client-facing solutions to better understand and measure these occurrences. I am currently exploring the paper linked here, but I would greatly appreciate any insights, experiences, or additional resources from the community that can help us refine our approach. If you have worked on similar projects or have knowledge of effective measurement tools, please share your expertise.
At my company we recently began an internal project to benchmark LLMs for hallucinations. We are building internal tools and tools for clients. I am curious if anybody has experience or can point me to papers or tools that help measure a hallucination. I am currently reading this https://arxiv.org/html/2512.22416v2 but wondering what experiences people have in the wild.
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