finding
active
finding:removing-the-scale-induced-information-leaves-24-implicationsRemoving the scale-induced information leaves 24 implications.
Number of implications after background knowledge removal.
Neighborhood — ranked by edge-count
Findings (1)
finding
- Empirical discovery via FCA that versus-relations on evolutionary tree leaves satisfy a single Horn rule with variables.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Key empirical result: removing four identified problematic data sources yields an 84% reduction.
- Author's emphasis on the interpretive nature of scaling.
- Implication of PRH: larger models should amplify bias less and hallucinate less if they better model reality
- Number of implications in the full stem base of the trees context.
- SAEs uncover safety-relevant representations that might be monitored or controlled.
- Central thesis: expanding an agent's sensors and goals outward to include others' states creates bidirectional feedback loop that scales intelligence and increases compassion.