DeepScaleR-Preview-Curated

DeepScaleR-Preview-Curated is a curated revision of the agentica-org/DeepScaleR-Preview-Dataset snapshot used for our Verl (GRPO) math-RL runs.

The published snapshot (226 entries, 220 unique problems) was reconciled against the maintainer's revision sheet for the next release: retracted problems were dropped, duplicate uploads were collapsed onto their first occurrence, corrected answers were taken as the authoritative ground truth, and the maintainer's new problems were appended. The result is 223 training rows.

Reconciliation statistics

published_entries: 226 published_unique: 220 final_rows: 223 answer_corrected: 11 no_change_corrections: 3 orphan_corrections: 2 retracted: 5 duplicate_removed: 6 added: 8

How the reconciliation was applied

• Retractions (retracted) are dropped entirely.
• Duplicate uploads (duplicate_removed) keep only the first occurrence in published file order, together with that first occurrence's solution text; the later copies' write-ups are discarded.
• Answer corrections (answer_corrected) replace the published answer with the maintainer's answer as ground truth. The solution text still comes from the published snapshot, since the revision sheet does not ship solutions.
• No-op corrections (no_change_corrections) supply an answer that already matches the published answer, so nothing is changed and they are counted here only.
• Orphan corrections (orphan_corrections) point at problems that do not exist in the published snapshot; no row is fabricated for them, they are only flagged in the report.
• Additions (added) are appended at the end in the maintainer's file order.

Final row order is the published order after the removals above, followed by the additions, with a fresh 0-based index over that order.

Files

• reconciliation_report.json — the changelog: the summary block above plus one entry per affected problem in conflicts (answer_corrected, orphan_correction, retracted, duplicate_removed, added), sorted by problem then type.
• verl_deepscaler_v2.parquet — the training file in Verl row format. Not hosted here: it stays on the training machine and goes straight into the Verl training run.

Verl row format

Each row carries data_source, prompt (a single user message holding the problem text), ability, reward_model (style: rule, ground_truth: <answer after reconciliation>), and extra_info (index, solution).

Intended use

Reward-model-style rule verification for GRPO/PPO math reasoning training with Verl — the same setup used to reproduce DeepSeek-R1's "aha moment" on a small model.

Source

Derived from agentica-org/DeepScaleR-Preview-Dataset (approximately 40,000 AIME/AMC/Omni-MATH/STILL problem-answer pairs), which is distributed under the MIT license.