We lifted 15 functions out of this paper's own repositories and ran 12 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| kipok/nemo-skills | canonical | 12 of 15 |
| Function | Status | Where it lives |
|---|---|---|
| calculate_chunk_indices | Ran | kipok/nemo-skills/nemo_skills/file_utils.py code served (permissive licence) · get_code("2e7aafbc230cb972") |
| determine_proof_status | Ran | kipok/nemo-skills/nemo_skills/code_execution/proof_utils.py code served (permissive licence) · get_code("dfb61cd2ac2b564a") |
| extract_code_output | Ran | kipok/nemo-skills/nemo_skills/code_execution/utils.py code served (permissive licence) · get_code("b4bbfbf06bb92de6") |
| extract_code_to_execute | Ran | kipok/nemo-skills/nemo_skills/code_execution/utils.py code served (permissive licence) · get_code("b75a1053974f21ce") |
| extract_proof_only | Ran | kipok/nemo-skills/nemo_skills/code_execution/proof_utils.py code served (permissive licence) · get_code("df5a88c92c8f57ce") |
| format_code_output | Ran | kipok/nemo-skills/nemo_skills/code_execution/utils.py code served (permissive licence) · get_code("b2186409cb2b7dfb") |
| get_logger_name | Ran | kipok/nemo-skills/nemo_skills/utils.py code served (permissive licence) · get_code("364d75dfb259e939") |
| import_score_module | Ran | kipok/nemo-skills/nemo_skills/evaluation/compute_group_score.py code served (permissive licence) · get_code("28ecc1878ccced7c") |
| init_wandb | Ran | kipok/nemo-skills/nemo_skills/utils.py code served (permissive licence) · get_code("a2afdfc356abe1d1") |
| jload | Ran | kipok/nemo-skills/nemo_skills/file_utils.py code served (permissive licence) · get_code("8c48543062658550") |
| load_metric_files | Ran | kipok/nemo-skills/nemo_skills/evaluation/compute_group_score.py code served (permissive licence) · get_code("6f55869f2815d973") |
| setup_logging | Ran | kipok/nemo-skills/nemo_skills/utils.py code served (permissive licence) · get_code("4261064eb4ec7756") |
| count_newlines | Not yet run | kipok/nemo-skills/nemo_skills/file_utils.py code served (permissive licence) · get_code("5b3c40e3214faf87") |
| load_config | Not yet run | kipok/nemo-skills/nemo_skills/conversion/hf_to_nemo_llama.py code served (permissive licence) · get_code("e74354657e62b51d") |
| load_config | Not yet run | kipok/nemo-skills/nemo_skills/conversion/hf_to_nemo_qwen.py code served (permissive licence) · get_code("de5cce096268a65e") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
This paper presents our winning submission to the AI Mathematical Olympiad - Progress Prize 2 (AIMO-2) competition. Our recipe for building state-of-the-art mathematical reasoning models relies on three key pillars. First, we create a large-scale dataset comprising 540K unique high-quality math problems, including olympiad-level problems, and their 3.2M long-reasoning solutions. Second, we develop a novel method to integrate code execution with long reasoning models through iterative training, generation, and quality filtering, resulting in 1.7M high-quality Tool-Integrated Reasoning solutions. Third, we create a pipeline to train models to select the most promising solution from many candidates. We show that such generative solution selection (GenSelect) can significantly improve upon majority voting baseline. Combining these ideas, we train a series of models that achieve state-of-the-art results on mathematical reasoning benchmarks. To facilitate further research, we release our code, models, and the complete OpenMathReasoning dataset under a commercially permissive license.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2504.16891")
get_code_for_paper("2504.16891")
have("2504.16891")
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