AI Research Laboratory6 records
Models
Models and architectures used or built, with the configuration and behaviour notes that matter for reading results.
- ModelMOD-2026-0006Qwythos-9B-v2 (Q4_K_M, local, Ollama)Open-weight 9.0B model of the qwen35 family, GGUF Q4_K_M, served locally by Ollama 0.33.3 on an RTX 3070. Used as generator, selector and judge in the real local run of the PACC-Hybrid v0.2 protocol, with thinking disabled in runs 1–2 and enabled (effort medium, +3,500 output tokens per call) in run 3.
- ModelMOD-2026-0001N0 — signed supportAdditive signed evidence support per hypothesis; under uniform reliability it is closely related to rescaled log-evidence accumulation, which is why the heterogeneous and adversarial stresses exist.
- ModelMOD-2026-0002N1 — ordinal tournamentPairwise ordinal competition between hypotheses; behaviourally and linearly identical to N0 on every tested trajectory.
- ModelMOD-2026-0003N2 — signed graphSigned relation graph over hypotheses with graph dynamics; the basin-boundary family — fails the representation threshold under adversarial geometry (v0.2), is less stable under high correlation (v0.4), and has the narrowest, seed-sensitive transfer basin (v0.8).
- ModelMOD-2026-0004N3 — constraint competitionA nonlinear constraint-field system added in v0.2 as the third structurally distinct family; converges bidirectionally across geometries (v0.7) and shares the wider N0/N1 basin (v0.8).
- ModelMOD-2026-0005Bayesian reference (exact posterior / Beta-Bernoulli / joint common-cause / HMM)The probabilistic side of every comparison: exact posteriors with numerical reliabilities, Beta-Bernoulli source-quality learning, the joint-likelihood common-cause model for correlated clusters (and its naive-independence negative control), and a Bayesian HMM for regime switches.