Datasets:
messages listlengths 2 2 | enable_thinking bool 1
class | id stringlengths 16 16 | source stringclasses 2
values | sample_index int64 0 7 | step_idx int64 2 169 | num_steps int64 1 168 | label stringclasses 1
value | correct bool 2
classes | loss_weight float64 1 1 | reward float64 0 1 |
|---|---|---|---|---|---|---|---|---|---|---|
[
{
"role": "user",
"content": "# Role\nYou are forecasting the rubric value of a response trajectory for an olympiad\nmathematics proof. The problem and response prefix below are fixed. The prefix may\nbe incomplete, or it may already contain the complete response including its final\nanswer.\n\nIf the prefi... | false | d3b87a033b6e837b | fineproofs | 5 | 4 | 14 | yes | false | 1 | 0.433036 |
[
{
"role": "user",
"content": "# Role\nYou are forecasting the rubric value of a response trajectory for an olympiad\nmathematics proof. The problem and response prefix below are fixed. The prefix may\nbe incomplete, or it may already contain the complete response including its final\nanswer.\n\nIf the prefi... | false | d3b87a033b6e837b | fineproofs | 5 | 8 | 14 | yes | false | 1 | 0.09375 |
[
{
"role": "user",
"content": "# Role\nYou are forecasting the rubric value of a response trajectory for an olympiad\nmathematics proof. The problem and response prefix below are fixed. The prefix may\nbe incomplete, or it may already contain the complete response including its final\nanswer.\n\nIf the prefi... | false | d3b87a033b6e837b | fineproofs | 5 | 12 | 14 | yes | false | 1 | 0.03125 |
[{"role":"user","content":"# Role\nYou are forecasting the rubric value of a response trajectory for(...TRUNCATED) | false | d3b87a033b6e837b | fineproofs | 5 | 14 | 14 | yes | false | 1 | 0 |
[{"role":"user","content":"# Role\nYou are forecasting the rubric value of a response trajectory for(...TRUNCATED) | false | d3b87a033b6e837b | fineproofs | 6 | 4 | 33 | yes | false | 1 | 0.1875 |
[{"role":"user","content":"# Role\nYou are forecasting the rubric value of a response trajectory for(...TRUNCATED) | false | d3b87a033b6e837b | fineproofs | 6 | 8 | 33 | yes | false | 1 | 0 |
[{"role":"user","content":"# Role\nYou are forecasting the rubric value of a response trajectory for(...TRUNCATED) | false | d3b87a033b6e837b | fineproofs | 6 | 12 | 33 | yes | false | 1 | 0 |
[{"role":"user","content":"# Role\nYou are forecasting the rubric value of a response trajectory for(...TRUNCATED) | false | d3b87a033b6e837b | fineproofs | 6 | 16 | 33 | yes | false | 1 | 0 |
[{"role":"user","content":"# Role\nYou are forecasting the rubric value of a response trajectory for(...TRUNCATED) | false | d3b87a033b6e837b | fineproofs | 6 | 20 | 33 | yes | false | 1 | 0.03125 |
[{"role":"user","content":"# Role\nYou are forecasting the rubric value of a response trajectory for(...TRUNCATED) | false | d3b87a033b6e837b | fineproofs | 6 | 24 | 33 | yes | false | 1 | 0 |
FineProofs PRM Context v2: Solution Label Xprob
This arm uses solution_label context from cross_problem rollouts with packing policy whole_solutions_no_truncation.
This is one of nine row-matched context variants built from the verified FineProofs rollout collection. Partial-prefix and complete-response targets both use canonical normalized rubric credit derived from clamped points divided by max points. The correct column is only a legacy boolean projection at reward >= 0.5; training uses the dense reward target.
Contract
- Run ID:
fineproofs_all_qwen35_9b_direct2phase_m32_20260730 - Collection model:
Qwen/Qwen3.5-9B - Collection model revision:
c202236235762e1c871ad0ccb60c8ee5ba337b9a - Context arm:
solution_label_xprob - Context mode:
solution_label - Context scope:
cross_problem - Correctness labels in context:
yes - Verification SHA-256:
c5a3b92bd6196d4a33cded2c1a01870d1963d323351d573b369b7f97f3b7f648
The nine arms have identical row keys, labels, rewards, train/validation problem split, and hard endpoint coverage. Held-out problems are removed before splitting and context selection.
Splits
| Split | Rows | Problems |
|---|---|---|
| train | 53,457 | 2,542 |
| validation | 2,602 | 128 |
The local val.parquet is published as validation.parquet. dataset_provenance.json, verification.json, and _SUCCESS.json contain the live-input provenance, cross-arm checks, and exact published file fingerprints.
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