concept
active
concept:binary-generation-constraintBinary Generation Constraint
Implementation technique zeroing all logits except Yes/No tokens to convert steering into binary cross-entropy
Neighborhood — ranked by edge-count
Methods (1)
method
- Optimization procedure that learns orthonormal basis vectors satisfying causal truth and retention constraints via composite loss
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.
- Used with GPT models to constrain responses to binary options (0/1) in belief coherence experiments.
- Abstract iterative scheme underlying Darwinian evolution, GP, and Dennett's tower of learning.
- Fundamental structure (G, M, R) modeling objects with attributes; gives rise to polar maps and concept lattices.
- Early stopping in alpha sweeps when mean fluency falls below 95% of baseline or >5% of responses fall below 90% baseline
- Fundamental discrete computation units used as neurons in DLGN and DiffLogic CA
- A vector subspace that causally impacts outputs only through the sign of its values, enabling harmless magnitude divergence
- Alternative explanation: models produce first-person experiential language by extending predictive text modeling of human-authored introspective writing without encoding it as roleplay