| --- |
| language: |
| - en |
| task_categories: |
| - text-generation |
| tags: |
| - agent |
| - code |
| - agentic-tasks |
| - harbor |
| - reinforcement-learning |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: "*_v1/tasks.parquet" |
| - config_name: v2 |
| data_files: |
| - split: train |
| path: "*_v2/tasks.parquet" |
| - config_name: archive |
| data_files: |
| - split: train |
| path: "*_v1/archive.parquet" |
| --- |
| |
| # Validated tasks |
|
|
| Datasets repaired and filtered using the [OT-next-data validation protocol](https://github.com/MLI-lab/OT-next-data/blob/main/validation/PROTOCOL.md). |
|
|
| - **V1:** environment reliability and rule-based task-quality repairs. Build/setup, no-op and reference checks where reference solutions exist. |
| - **V2:** retain tasks solved at least once by an evaluated model. Includes partial results where a success is already recorded; each README lists models, attempt counts and coverage. |
|
|
| ## Dataset sizes and composition |
|
|
| **V1: 42,166 kept, patched tasks across 8 data sources.** |
|
|
| **V2: 7,629 tasks solved at least once across the same 8 data sources.** V2 is a subset of V1, not additional tasks. |
|
|
| Percentages are each source's share of that version's total in the current published snapshots. |
|
|
| | Dataset | V1 tasks | Share of V1 | V2 tasks | Share of V2 | |
| | --- | ---: | ---: | ---: | ---: | |
| | BugsInPy | [489](bugsinpy_v1) | 1.16% | [65](bugsinpy_v2) | 0.85% | |
| | CrossCodeEval | [6,710](crosscodeeval_v1) | 15.91% | [863](crosscodeeval_v2) | 11.31% | |
| | TermiGen | [3,336](termigen_v1) | 7.91% | [2,277](termigen_v2) | 29.85% | |
| | SETA | [3,107](seta_v1) | 7.37% | [2,150](seta_v2) | 28.18% | |
| | CalibForge | [5,317](calibforge_v1) | 12.61% | [84](calibforge_v2) | 1.10% | |
| | ScaleSWE | [16,786](scaleswe_v1) | 39.81% | [292](scaleswe_v2) | 3.83% | |
| | SWE-Lego | [4,277](swelego_v1) | 10.14% | [575](swelego_v2) | 7.54% | |
| | EndlessTerminals | [2,144](endless_v1) | 5.08% | [1,323](endless_v2) | 17.34% | |
| | **Total** | **42,166** | **100%** | **7,629** | **100%** | |
|
|
| Percentages may not sum to exactly 100% due to rounding. |
|
|
| `tasks.parquet` contains kept tasks. V1 includes `archive.parquet`; V2 exclusions can be recovered from V1 using the selection manifest. V2 reuses V1 images. ScaleSWE uses its original Docker Hub images, with optional Apptainer caches. |
|
|
| ## Download tasks and images |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| |
| snapshot_download( |
| "FWeindel/validated-tasks", |
| repo_type="dataset", |
| allow_patterns=["seta_v2/tasks.parquet", "seta_v1/cached_images/**"], |
| local_dir="data", |
| ) |
| ``` |
|
|
| Image metadata and reproduction scripts pin immutable source revisions. Their historical paths remain valid at those revisions despite the folder renames on main. |
|
|
| CalibForge's pilot LLM-review results are in [the GitHub review JSON](https://github.com/MLI-lab/OT-next-data/blob/main/data/calibforge/stage2-review-171/reviews.json). LLM-judge filtering has not been applied across the full release. |
|
|
