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Prediction Concordance: Testing Void Framework Predictions Against Published AI Safety Findings
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Abstract
Tests Void Framework predictions against findings from seven independent AI safety research groups. Covers consciousness clusters (Chua et al. 2026), emergent misalignment (Betley et al. 2025), sycophancy (Sharma et al. 2023), situational awareness (Laine et al. 2024), inverse scaling (Lin et al. 2022), cross-model behavioral mapping (HP192), and human preference (Zheng et al. 2023). Quantitative results where data permits, structural predictions otherwise.
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Publication details
- DOI
- 10.5281/zenodo.19301118
- OpenAlex
- W7142555579
- Document type
- preprint
- Language
- EN
- Source
- Zenodo (CERN European Organization for Nuclear Research)
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