Datasets:
data_source stringclasses 4
values | prompt listlengths 2 2 | ability stringclasses 1
value | reward_model dict | extra_info dict |
|---|---|---|---|---|
code_taco | [
{
"role": "system",
"content": "You are an expert coding professional. You are given a self-contained code-related task instruction, which could include programming questions to solve, code snippets to analyse or candidates to compare. You should reason step-by-step about the task before arriving at a final... | code | {
"style": "rule",
"extraction_method": null,
"ground_truth": "{\"inputs\": [\"abc\\n3\\n1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\\n\", \"mmzhr\\n3\\n443 497 867 471 195 670 453 413 579 466 553 881 847 642 269 996 666 702 487 209 257 741 974 133 519 453\\n\", \"ajeeseerqnpaujubmajpibxrccazaawetywxmifze... | {
"id": "TACO_9e61bd10-5471-4b7f-af5e-374400d2d007",
"lower_pass_rate": 0,
"upper_pass_rate": 0.5
} |
code_primeintellect | [
{
"role": "system",
"content": "You are an expert coding professional. You are given a self-contained code-related task instruction, which could include programming questions to solve, code snippets to analyse or candidates to compare. You should reason step-by-step about the task before arriving at a final... | code | {
"style": "rule",
"extraction_method": null,
"ground_truth": "[{\"type\": \"stdin_stdout\", \"input\": \"RYBGRYBGR\\n\", \"output\": \"0 0 0 0\"}, {\"type\": \"stdin_stdout\", \"input\": \"!RGYB\\n\", \"output\": \"0 1 0 0\"}, {\"type\": \"stdin_stdout\", \"input\": \"!!!!YGRB\\n\", \"output\": \"1 1 1 1\"}, {\"... | {
"id": "PRIMEINTELLECT_27caff35-0e93-4779-96c7-6112eebe11f8",
"lower_pass_rate": 0,
"upper_pass_rate": 0.25
} |
code_taco | [
{
"role": "system",
"content": "You are an expert coding professional. You are given a self-contained code-related task instruction, which could include programming questions to solve, code snippets to analyse or candidates to compare. You should reason step-by-step about the task before arriving at a final... | code | {
"style": "rule",
"extraction_method": null,
"ground_truth": "{\"inputs\": [\"6\\n6 4 2 7 2 7\\n3\\n2 3 6\\n1 3 4\\n1 1 6\\n\", \"4\\n5 5 2 3\\n10\\n1 2 4\\n2 1 4\\n1 1 1\\n2 1 4\\n2 1 2\\n1 1 1\\n1 3 3\\n1 1 3\\n1 4 4\\n1 2 2\\n\", \"4\\n2 2 3 6\\n9\\n2 2 3\\n1 1 3\\n2 2 3\\n2 2 3\\n2 2 2\\n1 1 3\\n1 1 3\\n2 1 ... | {
"id": "TACO_b6f07cfc-cabe-4b80-9589-357a95953dc0",
"lower_pass_rate": 0.625,
"upper_pass_rate": 1
} |
code_primeintellect | [{"role":"system","content":"You are an expert coding professional. You are given a self-contained c(...TRUNCATED) | code | {"style":"rule","extraction_method":null,"ground_truth":"[{\"type\": \"stdin_stdout\", \"input\": \"(...TRUNCATED) | {"id":"PRIMEINTELLECT_739a699e-a25e-4ce0-92e0-85e91ef01a28","lower_pass_rate":0.0,"upper_pass_rate":(...TRUNCATED) |
code_taco | [{"role":"system","content":"You are an expert coding professional. You are given a self-contained c(...TRUNCATED) | code | {"style":"rule","extraction_method":null,"ground_truth":"{\"inputs\": [\"7\\n\\n1 1\\n3 3\\n2 2\\n\\(...TRUNCATED) | {
"id": "TACO_7acf251c-05f4-4148-a24e-c702e9115cec",
"lower_pass_rate": 0,
"upper_pass_rate": 0.625
} |
code_primeintellect | [{"role":"system","content":"You are an expert coding professional. You are given a self-contained c(...TRUNCATED) | code | {"style":"rule","extraction_method":null,"ground_truth":"[{\"type\": \"stdin_stdout\", \"input\": \"(...TRUNCATED) | {"id":"PRIMEINTELLECT_d8841f66-b019-4398-b93f-34a869a19f8c","lower_pass_rate":0.0,"upper_pass_rate":(...TRUNCATED) |
code_primeintellect | [{"role":"system","content":"You are an expert coding professional. You are given a self-contained c(...TRUNCATED) | code | {"style":"rule","extraction_method":null,"ground_truth":"[{\"type\": \"function_call\", \"fn_name\":(...TRUNCATED) | {"id":"PRIMEINTELLECT_cfc3ef0f-e251-4474-90b1-a627117d8e9f","lower_pass_rate":0.125,"upper_pass_rate(...TRUNCATED) |
code_primeintellect | [{"role":"system","content":"You are an expert coding professional. You are given a self-contained c(...TRUNCATED) | code | {"style":"rule","extraction_method":null,"ground_truth":"[{\"type\": \"stdin_stdout\", \"input\": \"(...TRUNCATED) | {"id":"PRIMEINTELLECT_5e6a7525-1ba9-43cc-b717-469c305cc304","lower_pass_rate":0.0,"upper_pass_rate":(...TRUNCATED) |
code_primeintellect | [{"role":"system","content":"You are an expert coding professional. You are given a self-contained c(...TRUNCATED) | code | {"style":"rule","extraction_method":null,"ground_truth":"[{\"type\": \"stdin_stdout\", \"input\": \"(...TRUNCATED) | {"id":"PRIMEINTELLECT_33e3a605-3602-4fb8-98c5-22005a1cca3c","lower_pass_rate":0.0,"upper_pass_rate":(...TRUNCATED) |
code_taco | [{"role":"system","content":"You are an expert coding professional. You are given a self-contained c(...TRUNCATED) | code | {"style":"rule","extraction_method":null,"ground_truth":"{\"inputs\": [\"4\\n1 1\\n999999999 1000000(...TRUNCATED) | {
"id": "TACO_64807842-b216-4dfd-a5fc-eb76086d11ff",
"lower_pass_rate": 0,
"upper_pass_rate": 0.125
} |
FinalMix3
A multi-task code reinforcement-learning mixture in the
verl RL prompt format: one code-generation
split plus a suite of auxiliary code-understanding tasks, so the same corpus drives
three training regimes.
It is OctoReasoner/FinalMix2
with three changes: every row now carries one uniform prompt format, the auxiliary
mix is rebalanced by ability, and four defects where a prompt contradicted the
grader that scores it are repaired. The rows themselves are otherwise the same
problems, with the same rule-verifiable rewards.
Splits
| Split | Rows | Contents | Use |
|---|---|---|---|
train_no_aux |
9,693 | code generation only (9,693 rows) | RL on code generation alone |
train_aux_cascade |
25,318 | all 15,625 auxiliary rows first, then the 9,693 code rows | cascade / curriculum RL (aux → code) |
train_aux_multitask |
25,318 | the same rows, interleaved | mixed multi-task RL |
validation |
481 | held-out code-generation problems | held-out code generation, for in-training validation |
test |
175 | LiveCodeBench-v6 problems | LiveCodeBench-v6, repaired (see below) |
Prompt format
Every row — code generation and auxiliary alike — is exactly two turns: a system turn
that is byte-identical across the whole dataset, and a user turn that opens with an
[INSTRUCTION] block naming the task and its answer format, and closes with a one-line
reminder of that format.
system: You are an expert coding professional. You are given a self-contained
code-related task instruction, ... Failure to follow this format will result
in immediate task failure. Do not output any other text after your final answer.
user: [INSTRUCTION]
Predict the big-O time complexity of the code below.
Reply in the format \boxed{X}, where X is the complexity in standard big-O
notation, e.g. \boxed{O(1)}, \boxed{O(n)}, ... Write exponents as **.
[/INSTRUCTION]
[CODE] ... [/CODE]
Remember to reply with your answer within \boxed{...}. Any other format will
be immediately rejected.
This replaces FinalMix2's 25 per-family system prompts and its two rival code-fencing
conventions. Answers are extracted last-wins (the last fenced python block, the last
\boxed{...}, or a JSON object with the named key), so reasoning before the answer is
free. The reminder's wording follows how each row is graded, not how it looks.
Auxiliary tasks
15,625 rows across 24 abilities. FinalMix2 budgeted its auxiliary mix per
source family (14 of them) while ability (24 values) was never a stratification key,
so rare abilities inside large families were crushed — code_io_output_from_input_mcq
held 4 rows. FinalMix3 rebalances with a floor of 400 and a cap of 1,200 per ability:
short abilities are topped back up from
OctoReasoner/CodeAuxTasks
(candidates must clear the same length, language and near-duplicate gates the mix used),
and over-cap abilities are trimmed keeping the most distinctive rows. The spread across
abilities falls from 549x to 5.6x.
| ability | rows |
|---|---|
code_io_input_from_output_mcq |
1,200 |
code_from_space_complexity_mcq |
1,200 |
coderpile_retrieval |
1,200 |
pick_codes_similar_to_reference |
1,200 |
predict_cwe_from_code_mcq |
1,020 |
code_change_localization |
836 |
code_from_time_complexity_mcq |
829 |
code_cputime_ranking |
817 |
variable_output_tracing |
735 |
code_io_output_from_input_direct |
707 |
code_memory_ranking |
593 |
code_compile_status_prediction |
583 |
localize_callable_from_cwe_mcq |
552 |
localize_callable_from_cwe_direct |
498 |
predict_cwe_from_code_catalog |
400 |
code_io_input_output_pairs_mcq |
400 |
time_complexity_from_code_mcq |
400 |
code_io_input_from_output_direct |
400 |
time_complexity_from_code_direct |
400 |
space_complexity_from_code_mcq |
400 |
space_complexity_from_code_direct |
400 |
code_verifiable_instruction_following_generation |
387 |
code_io_output_from_input_mcq |
252 |
code_verifiable_instruction_following_edit |
216 |
Code split
| Source | Rows | Share |
|---|---|---|
code_primeintellect |
5,241 | 54.1% |
code_contests_o |
2,538 | 26.2% |
code_taco |
1,721 | 17.8% |
code_lcbv5 |
193 | 2.0% |
Repairs carried over FinalMix2
Each of these is a case where the shipped prompt or ground truth contradicted the grader, so a correct answer could not score:
pick_codes_similar_to_referenceasked for a clustering (\boxed{(1, 2, 4), (3)}) while the gold is the flat list of positions equivalent to the reference and the scorer compares the set of integers in the answer — obeying the prompt scored 0.predict_cwe_from_code_mcqcapped answers at optionEwhile every row offers six options;Fwas the single most common gold answer.- Multi-letter CWE answers are compared by string equality, so the required alphabetical ordering is stated again (it had been dropped in an earlier rewrite).
- LiveCodeBench-v6 (
test): 63 of 175 rows are functional problems whose ground truth carried nofn_name, so the checker graded them as stdin/stdout and theclass Solutionanswer the prompt asks for scored 0 on every case.fn_nameis now set from the starter signature and the expected outputs are canonicalised to what the fn-call harness prints. Scored end to end through the real reward path: 0/63 before, 63/63 after.
One row (vartrace_2327) was dropped: it asks for the final value of a variable it never
names, and unlike the 16 similar rows it cannot be reconstructed.
Schema
Unchanged from FinalMix2:
| Field | Type | Notes |
|---|---|---|
data_source |
string | routes the reward function |
prompt |
list of {role, content} |
system + user, as above |
ability |
string | task category |
reward_model |
struct {style, extraction_method, ground_truth, key} |
scoring spec |
extra_info |
struct {id, lower_pass_rate, upper_pass_rate} |
per-example metadata |
Code-generation rows are scored by executing the model's program against hidden tests in a
sandbox; auxiliary rows by rule-based extraction against ground_truth.
Reproduction
python tasks/stratify_aux.py --src FinalMix2/data --out FinalMix2-strat/data \
--floor 400 --cap 1200
python tasks/unify_prompts.py --src FinalMix2-strat/data --out FinalMix3/data
python tasks/verify_unified_prompts.py --src FinalMix2-strat/data --out FinalMix3/data
The verifier checks every row: two turns with the byte-identical system prompt, one
[INSTRUCTION] block carrying the ability's defined text, a reminder matching how the row
is graded, the task content preserved verbatim from FinalMix2, and data_source /
ability / reward_model / extra_info and row order otherwise untouched.
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