| # TACO + LeetCode |
|
|
| ## Curation and category organization |
|
|
| We bring together filtered TACO and LeetCodeDataset problems, organize their |
| upstream tags into seven category-removal groups, and prepare SFT examples and |
| RL prompts with reward tests. The category information originates in the |
| upstream datasets; this portion was not newly labeled through our LLM API. |
|
|
| `overlap_categories` lists the mapped groups associated with a problem. An |
| ablation removes a problem if any of these groups matches the selected category. |
| `no_tags` identifies records without mapped tags. The original detailed SFT |
| labels remain in `raw_*` columns; the release mapping is in |
| [taxonomy.json](../metadata/taco_leetcode/taxonomy.json). |
|
|
| ## Splits and verification |
|
|
| The historical SFT pool contains 21,879 rows: 19,493 TACO and 2,386 |
| LeetCodeDataset. For this release, we hold out 100 unique-prompt problems using |
| seed 20260907 and source/category stratification, leaving 21,779 training rows. |
| The original SFT fields, membership, and order remain recoverable. |
|
|
| RL retains the original 17,249 train / 100 validation split and all reward tests. |
| Its training metadata marks 11,587 reference-execution-verified rows and 5,662 |
| structural-only rows; validation has 71 and 29 respectively. |
| These flags describe the recorded checks; structural validation alone does not |
| show that a reference solution passes the tests. |
|
|
| There is no train/validation ID or normalized-prompt overlap within each |
| configuration, according to the release validation report. However, 71 problems |
| in RL validation also occur in SFT training, and 48 problems in the new SFT |
| validation set occur in RL training. The configurations preserve separate |
| experiments, not a leakage-free shared SFT-to-RL partition. |
|
|
| ## Reusing the experimental subsets |
|
|
| The recorded size-matched historical SFT subsets contain 14,043 rows and RL |
| subsets contain 12,168. Release SFT subset exports exclude the new holdout and |
| therefore need not remain equal-size. Full-corpus configurations have the larger |
| counts listed above. Use recorded memberships rather than a new random sample |
| when reproducing those experiments. |
|
|
| ```bash |
| # Original 21,879-row SFT pool, in original order: |
| python scripts/build_taco_leetcode.py --arm full_sft --historical --output original.parquet |
| # Historical RL arm: |
| python scripts/build_taco_leetcode.py --kind rl --arm no_graph --output arm.parquet |
| ``` |
|
|
| Run these commands from the repository root. The build script also accepts a |
| frozen source export through `--source DIR`; it repackages the prepared data, |
| rather than collecting or filtering the upstream datasets from scratch. |
| Source records, IDs, and split hashes are in |
| [metadata/taco_leetcode/](../metadata/taco_leetcode/). |
|
|
