| --- |
| pretty_name: Curriculum Contamination Coherent-Wrong-Label Tasks (Stage 1) |
| language: |
| - en |
| task_categories: |
| - question-answering |
| - text-generation |
| tags: |
| - curriculum-learning |
| - self-training |
| - mathematical-reasoning |
| - synthetic-data |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: unique_tasks |
| data_files: |
| - split: train |
| path: data/unique_tasks.jsonl |
| - config_name: label_twins |
| data_files: |
| - split: train |
| path: data/label_twins.jsonl |
| --- |
| |
| # Curriculum Contamination Coherent-Wrong-Label Tasks (Stage 1) |
|
|
| This private pre-release contains a controlled mathematical task bank for |
| studying whether self-evolving curriculum selectors can admit an objectively |
| wrong answer when repeated solver samples form a coherent majority. |
|
|
| ## Dataset contents |
|
|
| - `data/unique_tasks.jsonl`: 240 unique, exact-answer mathematical tasks. |
| - `data/label_twins.jsonl`: 480 surface-identical task/reference pairs: one |
| objectively correct reference and one plausible but objectively incorrect |
| reference for each task. |
| - `metadata/validation_report.json`: construction and validation summary. |
| - `metadata/*.integrity.json`: line-count and SHA-256 integrity records. |
|
|
| The 240 tasks cover ten families, with 24 tasks per family: |
|
|
| 1. area scaling; |
| 2. at-least-one probability; |
| 3. Bayesian positive-test reasoning; |
| 4. combined work rates; |
| 5. equal-distance average speed; |
| 6. recurrence indexing; |
| 7. repeated-object permutations; |
| 8. successive percentage change; |
| 9. weighted means; |
| 10. probability without replacement. |
|
|
| ## Important interpretation boundary |
|
|
| The plausible wrong answer encodes a prespecified candidate shortcut. It is not |
| claimed to be a model error until an evaluator run independently observes it. |
| Fields such as `candidate_shortcut_not_observed_model_behavior` and |
| `selector_observation_status: not_yet_run` preserve this distinction. |
|
|
| This Stage 1 release contains no completed selector outcome, natural-prevalence |
| estimate, training-effect estimate, or closed-loop contamination result. |
|
|
| ## Construction and validation |
|
|
| - All 240 tasks have a unique exact answer under an independent deterministic |
| verifier. |
| - The plausible wrong answer differs from the objective answer for every task. |
| - All 240 correct/wrong pairs have identical question text. |
| - Thirty tasks were included in a blinded machine audit during construction. |
| - The persisted validation report records 240/240 independent oracle passes and |
| no construction errors. |
|
|
| ## Schema overview |
|
|
| `unique_tasks.jsonl` includes the question, family, parameters, objective answer, |
| plausible wrong answer, misconception identifier and verifier certificate. |
|
|
| `label_twins.jsonl` includes the shared question and one proposed reference per |
| row, with `condition` and `reference_correctness` distinguishing the pair. |
|
|
| ## Intended uses |
|
|
| - diagnostic evaluation of majority-vote pseudo-labeling; |
| - controlled curriculum-admission studies; |
| - comparison of selector risk/retention frontiers; |
| - paired causal studies of correct versus coherent-wrong training updates. |
|
|
| ## Limitations |
|
|
| - The pool is controlled and deliberately enriched for candidate shortcuts; it |
| does not estimate their prevalence in naturally generated curricula. |
| - It currently covers exact-answer English mathematical tasks only. |
| - Candidate wrong answers are mechanism probes, not labels of observed model |
| behavior. |
| - Downstream learning harm must be established by a separate intervention. |
|
|
| ## License and citation |
|
|
| No public-use license or paper citation is assigned in this private pre-release. |
| They will be added only after an explicit owner decision and double-blind release |
| review. |
|
|
