olympiad-math-eval
Long-horizon Reasoning Agent for Olympiad-Level Mathematical Problem Solving — Songyang Gao et al. (arXiv:2512.10739, 2025)
What this evaluates
This evaluation probes an agent's ability to solve complex, long-horizon mathematical problems requiring multi-step deduction, proof construction, and lemma-based reasoning. It tests performance across standard competition benchmarks (AIME, HMMT) and rigorous Olympiad-level contests (IMO, CNMO, CMO), focusing on non-geometry problems where novel proof paths are required.
Datasets
- AIME2025 — total ?; splits: test (-1)
- HMMT2025 Feb — total ?; splits: test (-1)
- IMO2025 — total ?; splits: test (-1)
- CNMO2025 — total ?; splits: test (-1)
- CMO2025 — total 6; splits: test (6)
Metrics
pass@1 (primary) — range: [0, 1]
- Unbiased pass@k estimator: E[1/k * sum_{i=1}^k I(solution_i is correct)]. Correctness is determined by fine-grained grading points via CompassVerifier (solution-based) or OPV (proof-based). For IMO2025, pass@4 is used instead.
Input / output format
Input: Mathematical competition problems (solution-based and proof-based), excluding geometry for IMO2025 and CNMO2025.
Output: Final mathematical solution or proof, generated via multi-round hierarchical decomposition and lemma-based memory management.
Scoring recipe
def compute_passk(predictions, k, verifier_type):
correct = []
for pred in predictions[:k]:
if verifier_type == 'solution':
correct.append(1 if CompassVerifier(pred) else 0)
else:
correct.append(1 if OPV(pred) else 0)
return sum(correct) / k
# Usage: k=1 for AIME/HMMT/CNMO/CMO; k=4 for IMO2025.
# For CMO2025, human experts grade per question (max 21 pts each, total 126).
Common pitfalls
- Geometry problems are explicitly excluded from IMO2025 and CNMO2025 evaluations.
- The pass@k value varies by dataset: pass@1 is used for AIME2025, HMMT2025, CNMO2025, and CMO2025, while pass@4 is strictly used for IMO2025.
- Two different verifiers are employed based on problem type: CompassVerifier for solution-based questions and OPV for proof-based questions.
Evidence (verbatim from paper)
For each sample, we perform 16 independent rollouts and use the unbiased pass@1 [chen2021evaluating] as the metric, except for IMO2025, which we use pass@4.
Citation
@misc{gao2025longhorizon,
title={Long-horizon Reasoning Agent for Olympiad-Level Mathematical Problem Solving},
author={Songyang Gao et al.},
year={2025},
note={arXiv:2512.10739}
}
1---2name: olympiad-math-eval3description: This evaluation probes an agent's ability to solve complex, long-horizon mathematical problems requiring multi-step deduction, proof construction, and lemma-based reasoning. It tests performance across standard competition benchmarks (AIME, HMMT) and rigorous Olympiad-level contests (IMO, CNMO, CMO), focusing on non-geometry problems where novel proof paths are required. Use when the user wants to benchmark on AIME2025, HMMT2025 Feb, IMO2025, CNMO2025, CMO2025, or asks about evaluating this task. Reports pass@1.4---56# olympiad-math-eval78> Long-horizon Reasoning Agent for Olympiad-Level Mathematical Problem Solving — Songyang Gao et al. (arXiv:2512.10739, 2025)910## What this evaluates1112This evaluation probes an agent's ability to solve complex, long-horizon mathematical problems requiring multi-step deduction, proof construction, and lemma-based reasoning. It tests performance across standard competition benchmarks (AIME, HMMT) and rigorous Olympiad-level contests (IMO, CNMO, CMO), focusing on non-geometry problems where novel proof paths are required.1314## Datasets1516- **AIME2025** — total ?; splits: test (-1)17- **HMMT2025 Feb** — total ?; splits: test (-1)18- **IMO2025** — total ?; splits: test (-1)19- **CNMO2025** — total ?; splits: test (-1)20- **CMO2025** — total 6; splits: test (6)2122## Metrics2324- `pass@1` **(primary)** — range: [0, 1]25 - Unbiased pass@k estimator: E[1/k * sum_{i=1}^k I(solution_i is correct)]. Correctness is determined by fine-grained grading points via CompassVerifier (solution-based) or OPV (proof-based). For IMO2025, pass@4 is used instead.2627## Input / output format2829**Input**: Mathematical competition problems (solution-based and proof-based), excluding geometry for IMO2025 and CNMO2025.3031**Output**: Final mathematical solution or proof, generated via multi-round hierarchical decomposition and lemma-based memory management.3233## Scoring recipe3435```python36def compute_passk(predictions, k, verifier_type):37 correct = []38 for pred in predictions[:k]:39 if verifier_type == 'solution':40 correct.append(1 if CompassVerifier(pred) else 0)41 else:42 correct.append(1 if OPV(pred) else 0)43 return sum(correct) / k44# Usage: k=1 for AIME/HMMT/CNMO/CMO; k=4 for IMO2025.45# For CMO2025, human experts grade per question (max 21 pts each, total 126).46```4748## Common pitfalls4950- Geometry problems are explicitly excluded from IMO2025 and CNMO2025 evaluations.51- The pass@k value varies by dataset: pass@1 is used for AIME2025, HMMT2025, CNMO2025, and CMO2025, while pass@4 is strictly used for IMO2025.52- Two different verifiers are employed based on problem type: CompassVerifier for solution-based questions and OPV for proof-based questions.5354## Evidence (verbatim from paper)5556> For each sample, we perform 16 independent rollouts and use the unbiased pass@1 [chen2021evaluating] as the metric, except for IMO2025, which we use pass@4.5758## Citation5960```bibtex61@misc{gao2025longhorizon,62 title={Long-horizon Reasoning Agent for Olympiad-Level Mathematical Problem Solving},63 author={Songyang Gao et al.},64 year={2025},65 note={arXiv:2512.10739}66}67```6869- arXiv: 2512.10739