Runtime Fisher Spectral Sensitivity for Early Hallucination Detection in Edge-Deployed Language Models | Zenodo
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Kerimov-Alekberli model
Published July 2, 2026
| Version 1.4
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Runtime Fisher Spectral Sensitivity for Early Hallucination Detection in Edge-Deployed Language Models
Authors/Creators
Alekberli, Rahid<br>(Researcher)1
Karimov, Hikmat<br>(Researcher)1
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1.
Azerbaijan Technical University
Description
We study whether the spectral sensitivity of the per-token empirical Fisher Information Matrix (FIM), ωmax(Ft), can serve as a lightweight, model-agnostic runtime signal for anticipating hallucination during autoregressive decoding on consumer edge hardware. Across four pre-registered experiments on twelve open-weight models run locally via Ollama and MLX on an Apple M5 (32GB unified memory), we establish, in turn: cross-run stability of the signal, its predictive correlation with hallucination onset, its early-warning lead time, and the e!ectiveness of an intervention triggered by the resulting alarm. Concretely, ten of twelve models satisfy a stability gate (coe”cient of variation Files
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Additional details
Software
Repository URL
https://doi.org/10.5281/zenodo.21141999
Programming language
Python
Development Status
Active
References
J. Pennington and P. Worah, "The spectrum of the Fisher information matrix of a single- hidden-layer neural network," in Advances in Neural Information Processing Systems (NeurIPS), 2018. https://proceedings.neurips.cc/paper_files/paper/2018/file/18bb68e2b38e4a8ce7cf4f6b2625768c-Paper.pdf
S. Kadavath et al., "Language models (mostly) know what they know," arXiv preprint arXiv:2207.05221, 2022. https://doi.org/10.48550/arXiv.2207.05221
S. Farquhar et al., "Detecting hallucinations in large language models using semantic entropy," Nature, vol. 630, 2024. https://doi.org/10.1038/s41586-024-07421-0
O. Shorinwa et al., "A survey on uncertainty quantification of large language models: taxonomy, open research challenges, and future directions," arXiv preprint, 2025. https://doi.org/10.48550/arXiv.2412.05563
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Keywords and subjects
Keywords
Fisher information
hallucination detection
runtime monitoring
on-device inference
quantization
large language models
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DOI
10.5281/zenodo.21133067
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Resource type<br>Preprint
Publisher<br>Zenodo
Languages
English
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Creative Commons Attribution 4.0 International
The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited.
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Copyright
Hikmat Kerimov and Rahid Zahid Alekberli
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Created
July 2, 2026
Modified
July 2, 2026
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