Q8-CLUSTER-119: YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain — E8 Intelligence Research
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Abstract
Q8 Compression Breakthrough — Cluster 119 of 240 E8 root vectors. Compression ratio: 1.000 (threshold: 0.72) Cluster size: 19 discoveries Domain: geometry E8 root vector bucket: 119/240 Source discoveries: - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
Publication details
- DOI
- 10.5281/zenodo.20436306
- OpenAlex
- W7162694129
- Document type
- preprint
- Language
- EN
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- Zenodo (CERN European Organization for Nuclear Research)
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