Mathesis: Regression-Gated Continual Personalisation of Local Language Models
A regression-gated continual personalisation pipeline for local language models using isolated LoRA candidates.
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01 - Overview
Overview
Mathesis studies how approved corrections can become isolated LoRA candidates for a local language model without mutating the parent model.
Mathesis completed a checksum-verified three-seed controlled study on Qwen3-1.7B. Two independently trained LoRA adapters passed all eight predeclared activation gates, while one high-accuracy candidate was rejected because it introduced a contradiction.
02 - Activation gates
Activation gates
A candidate is accepted only when every predeclared gate passes: target learning, prior-lesson retention, general capability, contradiction, scope error, safety, provenance, and tensor integrity.
The seed-17 result is the key counterexample: aggregate accuracy alone would have accepted it, but the contradiction gate correctly forced rollback.
03 - Evidence boundary
Evidence boundary
This is a successful controlled proof-of-concept, not a claim of universal personalisation.
The study uses generated template-related English examples, one pinned 1.7B base model, three seeds, and no human participants.
04 - Findings
What the release demonstrates.
- Unmodified base model scored 29/60 on the frozen final suite; the static all-lessons prompt scored 51/60.
- LoRA seeds 42 and 73 reached 60/60 and passed every activation gate.
- LoRA seed 17 reached 59/60 but was rejected because the contradiction gate caught one reversal.
- The accepted seed-42 demonstration adapter corrected 31 base failures with 0 base successes lost.
- The compact general sentinel stayed unchanged at 5/8 for the accepted seed-42 adapter.
- The exact paired McNemar result against base for seed 42 was p = 9.31 x 10^-10 on the fixed controlled suite.
05 - Prototype
Selected system details.
Reported statistics describe the fixed controlled suite and should not be read as population-level estimates or general safety certification.