| --- |
| pretty_name: Procedural Pile |
| license: cc-by-4.0 |
| task_categories: |
| - text-generation |
| - question-answering |
| language: |
| - en |
| dataset_info: |
| features: |
| - name: task |
| dtype: large_string |
| - name: prompt |
| dtype: large_string |
| - name: answer |
| dtype: large_string |
| - name: metadata |
| dtype: large_string |
| - name: level |
| dtype: int64 |
| - name: mode |
| dtype: large_string |
| tags: |
| - reasoning |
| - procedural |
| - synthetic |
| - pretraining |
| - formal |
| size_categories: |
| - 10M<n<100M |
| --- |
| |
| <p align="center"> |
| <img src="https://imgshare.cc/api/image/proxy?id=443lb70v" alt="Procedural Pile: verifiable procedural data optimized for transferability" width="100%"> |
| </p> |
|
|
| <p align="center"> |
| <a href="https://github.com/sileod/reasoning_core/blob/main/GALLERY.md">Task gallery</a> · |
| <a href="https://github.com/sileod/reasoning_core">Source</a> · |
| <a href="https://huggingface.co/papers/2509.18083">Paper</a> · |
| <a href="https://huggingface.co/datasets/reasoning-core/rc1">RLVR dataset</a> |
| </p> |
|
|
| Procedural Pile is a synthetic corpus of verifiable reasoning problems generated by [Reasoning Core](https://github.com/sileod/reasoning_core). It is intended for continued pretraining, mid-training, and supervised fine-tuning. |
|
|
| Answers come from procedural generators and task-specific solvers or checkers, rather than language-model generation. The corpus spans mathematics, formal logic, planning, graphs, parsing, code, structured data, and other symbolic domains. Difficulty is controlled continuously within each task. |
|
|
| Reasoning Core is optimized for transferability: task selection and difficulty ranges are guided by reproducible measurements of transfer, solvability, and shortcut resistance. |
|
|
| --- |
|
|
| ## Load |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("reasoning-core/procedural-pile") |
| ``` |
|
|
| No configuration name is required. The dataset provides `train` and `test` splits. |
|
|
| ## Dataset structure |
|
|
| | Field | Description | |
| |---|---| |
| | `task` | Reasoning task identifier | |
| | `prompt` | Model input | |
| | `answer` | Canonical target answer | |
| | `metadata` | JSON-encoded generation and validation metadata | |
| | `level` | Difficulty level | |
| | `mode` | `instruct`, `few_shot`, or `verification` | |
|
|
| Most examples use direct instruction format. A smaller share adds one in-context demonstration or asks the model to verify a candidate answer. |
|
|
| --- |
|
|
| ## Task catalogue |
|
|
| The corpus currently contains 50 task families. The [task gallery](https://github.com/sileod/reasoning_core/blob/main/GALLERY.md) includes a worked example for each one. |
|
|
| | Area | Tasks | |
| |---|---| |
| | **Mathematics & formal methods** · 10 | `arithmetics` · `math_word_problem` · `equation_system` · `combinatorics_formula_selection` · `planar_geometry_relations` · `lean_candidate_compilation` · `lean_missing_line` · `metamath_core_select` · `metamath_entailment` · `sequential_induction` | |
| | **Logic & inference** · 10 | `logic_formalization` · `logic_nli` · `logic_qa` · `defeasible_nli` · `multistep_nli` · `multistep_abduction` · `multistep_evidence_retrieval` · `qualitative_reasoning` · `qualitative_causal_reasoning` · `belief_tracking` | |
| | **Symbolic transformations** · 7 | `lambda_reduction` · `rewrite_system` · `unification_entailment` · `set_expression` · `set_missing_element` · `string_transduction` · `analogical_case_matching` | |
| | **Planning, state & graphs** · 7 | `planning` · `constraint_satisfaction` · `grid_navigation` · `reference_tracking` · `coreference` · `graph_pathfinding` · `graph_successors` | |
| | **Language & formal languages** · 5 | `parsing_derivation` · `regex_following` · `regex_reasoning` · `constrained_continuation` · `syntax_error_detection` | |
| | **Structured data & code** · 7 | `table_qa` · `table_equivalence` · `table_statistics` · `code_analysis` · `code_execution` · `code_runnability` · `program_synthesis` | |
| | **Games & probability** · 4 | `game_best_move` · `game_forced_win` · `most_probable_evidence` · `most_probable_outcome` | |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{reasoningcore2026, |
| title = {Reasoning Core: A Scalable Procedural Data Generation Suite for Symbolic Pre-training and Post-Training}, |
| author = {Lacombe, Valentin and Quesnel, Valentin and Sileo, Damien}, |
| journal = {arXiv preprint arXiv:2603.02208}, |
| year = {2026}, |
| url = {https://arxiv.org/abs/2603.02208} |
| } |
| ``` |
|
|
