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This equation captures one of the core mathematical components of the system. vt = log det(Σ′) = X i log λi where λi are eigenvalues of Σ′. We use log-
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Learning Uncertainty from Sequential Internal Dispersion in Large Language Models explores SIVR detects LLM hallucinations by learning from the dispersion of internal representations across layers, offering a model-agnostic and generalizable solution.. Commercial viability score: 8/10 in LLM Hallucination Detection.
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Canonical route: /paper/learning-uncertainty-from-sequential-internal-dispersion-in-large-language-models
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Canonical ID learning-uncertainty-from-sequential-internal-dispersion-in-large-language-models | Route /paper/learning-uncertainty-from-sequential-internal-dispersion-in-large-language-models
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/buildability/learning-uncertainty-from-sequential-internal-dispersion-in-large-language-models
Subject: Learning Uncertainty from Sequential Internal Dispersion in Large Language Models
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Receipt path
/buildability/learning-uncertainty-from-sequential-internal-dispersion-in-large-language-models
Paper ref
learning-uncertainty-from-sequential-internal-dispersion-in-large-language-models
arXiv id
2604.15741
Generated at
2026-04-20T20:23:08.989Z
Evidence freshness
stale
Last verification
2026-04-20T20:23:08.989Z
Sources
4
References
0
Coverage
67%
Lineage hash
bbe69281c4a097655e28d696fb8e2cc39b1d29b62c5df920769f367b4e367588
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Pending verification refs / 4 sources / Verification pending
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Dimensions overall score 8.0
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This equation captures one of the core mathematical components of the system. vt = log det(Σ′) = X i log λi where λi are eigenvalues of Σ′. We use log-
Page and bbox are available; crop image is pending.
This equation captures one of the core mathematical components of the system. ance Σ′ = Σ + αId for some small α > 0. We
Page and bbox are available; crop image is pending.
This equation captures one of the core mathematical components of the system. L X l=0 ˆhl t ct = 1 − Notably, circular variance also contains infor- matio
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