this post was submitted on 11 Mar 2026
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How Much Do LLMs Hallucinate in Document Q&A Scenarios? A 172-Billion-Token Study Across Temperatures, Context Lengths, and Hardware Platforms [TLDR: 25%] (arxiv.org)
submitted 4 hours ago* (last edited 4 hours ago) by RandAlThor@lemmy.ca to c/technology@lemmy.world
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Evaluating 35 open-weight models across three context lengths (32K, 128K, 200K), four temperatures, and three hardware platforms—consuming 172 billion tokens across more than 4,000 runs—we find that the answer is “substantially, and unavoidably.” Even under optimal conditions—best model, best temperature, temperature chosen specifically to minimize fabrication—the floor is non-zero and rises steeply with context length. At 32K, the best model (GLM 4.5) fabricates 1.19% of answers, top-tier models fabricate 5–7%, and the median model fabricates roughly 25%.

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[–] FauxLiving@lemmy.world 2 points 1 hour ago

Calculators are not computers, computers contain calculator-like elements but a calculator is no more a computer than a passenger jet is a coffee shop by virtue of having a coffee pot onboard.

Calculators cannot fabricate answers, but nor are they 100% correct due to things like bitflips and square root approximations. They also cannot write text, so the comparison would make even less sense.

LLMs and Humans can fabricate answers in written text so comparing the fabrication rate in written text of an LLM to a human (both entities which generate their answers with neural networks) makes more sense than to compare either to a calculator which neither uses a neural network or produces text.

So 'we' should compare like things and not choose items based on superficial similarities.