Technical Manual for Toolkit for Confidence-Corpus Consistency, Corpus Absorption and Rule Learning via Fine-Tuning on a Fabricated Corpus
This manual documents version 2.0.0 of an open toolkit for fine-tuning small causal language models on fabricated and rule-governed arithmetic corpora and measuring what they take up from them. The fact domain is the 81 additions of two single-digit natural numbers, small enough to be enumerated exhaustively. The toolkit fine-tunes a model on the correct sums, on one fixed fabricated answer for every addition, and back on the correct sums of a subset of the additions; it fine-tunes copies of these models on simple rules (the sum plus a constant) and on a conditional rule (a shift that depends on the order of the addends), each paired with a control that has the same answers but no rule; a...
| Authors | José Luciano Verçosa Marques, Frederico Jorge Heitmann, Daniel Omar Perez et al. |
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| Primary category | cs.CL |
| Published | 23 September 2026 |
| Last updated at source | 5 October 2026 |
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