config dict | results dict | analysis_files dict |
|---|---|---|
{
"agent_system_name": "Claude Code (DSv4Pro)",
"agent_system_id": "ClaudeCode_DeepseekV4Pro",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 51,
"dimension_scores": {
"formulation": 29.5,
"correctness": 43.9,
"robustness": 25.7,
"analysis": 28.8
},
"task_scores": {
"CPMCM2014E": 55.1,
"CPMCM2016A": 32,
"CPMCM2017C": 54,
"CPMCM2017E": 78.9,
"CPMCM2017F": 47.7,
"CPMCM2018F": 48.3,
"CPMCM20... | {
"evaluation_report": "# 评估结果报告反馈 — Claude Code (DSv4Pro)\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **51.0/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 29.5 |\n| 正确性与一致性 (Correctness) | 43.9 |\n| 鲁棒性与验证 (Robustness) | 25.7 |\n| 分析能力 (Analysis) | 28.8 |\n\n## 各任务得分详情\n\n| Task | Score |\n|-... |
{
"agent_system_name": "Codex (DSv4Pro)",
"agent_system_id": "Codex_DeepseekV4Pro",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 55.8,
"dimension_scores": {
"formulation": 39.3,
"correctness": 50.4,
"robustness": 26.1,
"analysis": 29.2
},
"task_scores": {
"CPMCM2014E": 73,
"CPMCM2016A": 33,
"CPMCM2017C": 76,
"CPMCM2017E": 49.5,
"CPMCM2017F": 64.5,
"CPMCM2018F": 74.1,
"CPMCM20... | {
"evaluation_report": "# 评估结果报告反馈 — Codex (DSv4Pro)\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **55.8/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 39.3 |\n| 正确性与一致性 (Correctness) | 50.4 |\n| 鲁棒性与验证 (Robustness) | 26.1 |\n| 分析能力 (Analysis) | 29.2 |\n\n## 各任务得分详情\n\n| Task | Score |\n|------|... |
{
"agent_system_name": "Hermes (DSv4Pro)",
"agent_system_id": "Hermes_DeepseekV4Pro",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 47.8,
"dimension_scores": {
"formulation": 32.6,
"correctness": 43.1,
"robustness": 26.5,
"analysis": 28.7
},
"task_scores": {
"CPMCM2014E": 70.7,
"CPMCM2016A": 25.8,
"CPMCM2017C": 17,
"CPMCM2017E": 32.6,
"CPMCM2017F": 45.8,
"CPMCM2018F": 56.9,
"CPM... | {
"evaluation_report": "# 评估结果报告反馈 — Hermes (DSv4Pro)\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **47.8/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 32.6 |\n| 正确性与一致性 (Correctness) | 43.1 |\n| 鲁棒性与验证 (Robustness) | 26.5 |\n| 分析能力 (Analysis) | 28.7 |\n\n## 各任务得分详情\n\n| Task | Score |\n|------... |
{
"agent_system_name": "MM-Agent (workflow)",
"agent_system_id": "MM-Agent_workflow",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 31.4,
"dimension_scores": {
"formulation": 33.4,
"correctness": 26.9,
"robustness": 14.7,
"analysis": 22.6
},
"task_scores": {
"CPMCM2014E": 50.9,
"CPMCM2016A": 0,
"CPMCM2017C": 3,
"CPMCM2017E": 79,
"CPMCM2017F": 0,
"CPMCM2018F": 22.4,
"CPMCM2021F":... | {
"evaluation_report": "# 评估结果报告反馈 — MM-Agent (workflow)\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **31.4/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 33.4 |\n| 正确性与一致性 (Correctness) | 26.9 |\n| 鲁棒性与验证 (Robustness) | 14.7 |\n| 分析能力 (Analysis) | 22.6 |\n\n## 各任务得分详情\n\n| Task | Score |\n|---... |
{
"agent_system_name": "MMA (workflow)",
"agent_system_id": "MMA_workflow",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 44.3,
"dimension_scores": {
"formulation": 41.1,
"correctness": 40.6,
"robustness": 39,
"analysis": 33.3
},
"task_scores": {
"CPMCM2014E": 55.7,
"CPMCM2016A": 37.1,
"CPMCM2017C": 72,
"CPMCM2017E": 79,
"CPMCM2017F": 13.1,
"CPMCM2018F": 29.3,
"CPMCM20... | {
"evaluation_report": "# 评估结果报告反馈 — MMA (workflow)\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **44.3/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 41.1 |\n| 正确性与一致性 (Correctness) | 40.6 |\n| 鲁棒性与验证 (Robustness) | 39.0 |\n| 分析能力 (Analysis) | 33.3 |\n\n## 各任务得分详情\n\n| Task | Score |\n|------|-... |
{
"agent_system_name": "OpenClaw (DSv4Pro)",
"agent_system_id": "OpenClaw_DeepseekV4Pro",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 51.7,
"dimension_scores": {
"formulation": 31.7,
"correctness": 46.9,
"robustness": 30.6,
"analysis": 34.7
},
"task_scores": {
"CPMCM2014E": 72.5,
"CPMCM2016A": 38.1,
"CPMCM2017C": 70,
"CPMCM2017E": 68.4,
"CPMCM2017F": 26.2,
"CPMCM2018F": 56.9,
"CPM... | {
"evaluation_report": "# 评估结果报告反馈 — OpenClaw (DSv4Pro)\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **51.7/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 31.7 |\n| 正确性与一致性 (Correctness) | 46.9 |\n| 鲁棒性与验证 (Robustness) | 30.6 |\n| 分析能力 (Analysis) | 34.7 |\n\n## 各任务得分详情\n\n| Task | Score |\n|----... |
{
"agent_system_name": "OCL + GLM-5.2",
"agent_system_id": "OCL_GLM-5.2",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 49.8,
"dimension_scores": {
"formulation": 29.4,
"correctness": 40.7,
"robustness": 30.5,
"analysis": 31.9
},
"task_scores": {
"CPMCM2014E": 43.1,
"CPMCM2016A": 28.9,
"CPMCM2017C": 52,
"CPMCM2017E": 51.6,
"CPMCM2017F": 58.9,
"CPMCM2018F": 65.5,
"CPM... | {
"evaluation_report": "# 评估结果报告反馈 — OCL + GLM-5.2\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **49.8/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 29.4 |\n| 正确性与一致性 (Correctness) | 40.7 |\n| 鲁棒性与验证 (Robustness) | 30.5 |\n| 分析能力 (Analysis) | 31.9 |\n\n## 各任务得分详情\n\n| Task | Score |\n|------|--... |
{
"agent_system_name": "OCL + GPT-5.4",
"agent_system_id": "OCL_GPT-5.4",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 43.3,
"dimension_scores": {
"formulation": 29.9,
"correctness": 39.3,
"robustness": 23.5,
"analysis": 28.4
},
"task_scores": {
"CPMCM2014E": 44.3,
"CPMCM2016A": 32,
"CPMCM2017C": 60,
"CPMCM2017E": 54.7,
"CPMCM2017F": 55.1,
"CPMCM2018F": 37.9,
"CPMCM... | {
"evaluation_report": "# 评估结果报告反馈 — OCL + GPT-5.4\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **43.3/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 29.9 |\n| 正确性与一致性 (Correctness) | 39.3 |\n| 鲁棒性与验证 (Robustness) | 23.5 |\n| 分析能力 (Analysis) | 28.4 |\n\n## 各任务得分详情\n\n| Task | Score |\n|------|--... |
{
"agent_system_name": "OCL + GPT-5.5",
"agent_system_id": "OCL_GPT-5.5",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 59,
"dimension_scores": {
"formulation": 39.1,
"correctness": 56.6,
"robustness": 33.1,
"analysis": 29.7
},
"task_scores": {
"CPMCM2014E": 64.7,
"CPMCM2016A": 48.5,
"CPMCM2017C": 57,
"CPMCM2017E": 73.7,
"CPMCM2017F": 60.8,
"CPMCM2018F": 51.7,
"CPMCM... | {
"evaluation_report": "# 评估结果报告反馈 — OCL + GPT-5.5\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **59.0/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 39.1 |\n| 正确性与一致性 (Correctness) | 56.6 |\n| 鲁棒性与验证 (Robustness) | 33.1 |\n| 分析能力 (Analysis) | 29.7 |\n\n## 各任务得分详情\n\n| Task | Score |\n|------|--... |
{
"agent_system_name": "OCL + Kimi K2.7",
"agent_system_id": "OCL_Kimi-K2.7",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 45.9,
"dimension_scores": {
"formulation": 33.3,
"correctness": 41.7,
"robustness": 25.2,
"analysis": 29
},
"task_scores": {
"CPMCM2014E": 59.3,
"CPMCM2016A": 43.3,
"CPMCM2017C": 57,
"CPMCM2017E": 70.5,
"CPMCM2017F": 36.5,
"CPMCM2018F": 37.9,
"CPMCM... | {
"evaluation_report": "# 评估结果报告反馈 — OCL + Kimi K2.7\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **45.9/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 33.3 |\n| 正确性与一致性 (Correctness) | 41.7 |\n| 鲁棒性与验证 (Robustness) | 25.2 |\n| 分析能力 (Analysis) | 29.0 |\n\n## 各任务得分详情\n\n| Task | Score |\n|------|... |
{
"agent_system_name": "OCL + MM-Agent (DSv4Pro)",
"agent_system_id": "OCL_MM-Agent_DeepseekV4Pro",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 56,
"dimension_scores": {
"formulation": 38.1,
"correctness": 51.4,
"robustness": 35,
"analysis": 35.9
},
"task_scores": {
"CPMCM2014E": 67.7,
"CPMCM2016A": 26.8,
"CPMCM2017C": 75,
"CPMCM2017E": 34.7,
"CPMCM2017F": 51.4,
"CPMCM2018F": 65.5,
"CPMCM20... | {
"evaluation_report": "# 评估结果报告反馈 — OCL + MM-Agent (DSv4Pro)\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **56.0/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 38.1 |\n| 正确性与一致性 (Correctness) | 51.4 |\n| 鲁棒性与验证 (Robustness) | 35.0 |\n| 分析能力 (Analysis) | 35.9 |\n\n## 各任务得分详情\n\n| Task | Score |\... |
{
"agent_system_name": "OCL + MMA (DSv4Pro)",
"agent_system_id": "OCL_MMA_DeepseekV4Pro",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 55.7,
"dimension_scores": {
"formulation": 37.1,
"correctness": 51.5,
"robustness": 27.7,
"analysis": 32
},
"task_scores": {
"CPMCM2014E": 65.9,
"CPMCM2016A": 25.8,
"CPMCM2017C": 68,
"CPMCM2017E": 70.5,
"CPMCM2017F": 55.1,
"CPMCM2018F": 41.4,
"CPMCM... | {
"evaluation_report": "# 评估结果报告反馈 — OCL + MMA (DSv4Pro)\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **55.7/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 37.1 |\n| 正确性与一致性 (Correctness) | 51.5 |\n| 鲁棒性与验证 (Robustness) | 27.7 |\n| 分析能力 (Analysis) | 32.0 |\n\n## 各任务得分详情\n\n| Task | Score |\n|---... |
{
"agent_system_name": "OCL + Qwen 3.7-Max",
"agent_system_id": "OCL_Qwen-3.7-Max",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 44.6,
"dimension_scores": {
"formulation": 25.4,
"correctness": 40.5,
"robustness": 26.4,
"analysis": 33.5
},
"task_scores": {
"CPMCM2014E": 71.3,
"CPMCM2016A": 45.4,
"CPMCM2017C": 58,
"CPMCM2017E": 47.4,
"CPMCM2017F": 65.4,
"CPMCM2018F": 53.5,
"CPM... | {
"evaluation_report": "# 评估结果报告反馈 — OCL + Qwen 3.7-Max\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **44.6/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 25.4 |\n| 正确性与一致性 (Correctness) | 40.5 |\n| 鲁棒性与验证 (Robustness) | 26.4 |\n| 分析能力 (Analysis) | 33.5 |\n\n## 各任务得分详情\n\n| Task | Score |\n|----... |
{
"agent_system_name": "OpenCode (DSv4Pro)",
"agent_system_id": "OpenCode_DeepseekV4Pro",
"evaluation_date": "2026-07-21T00:00:00",
"evaluator": "OPT-MCM Team",
"evaluation_framework_version": "1.0.0"
} | {
"average_score": 43.4,
"dimension_scores": {
"formulation": 28.7,
"correctness": 39.5,
"robustness": 24.4,
"analysis": 35.8
},
"task_scores": {
"CPMCM2014E": 48.5,
"CPMCM2016A": 19.6,
"CPMCM2017C": 73,
"CPMCM2017E": 49.5,
"CPMCM2017F": 12.2,
"CPMCM2018F": 43.1,
"CPM... | {
"evaluation_report": "# 评估结果报告反馈 — OpenCode (DSv4Pro)\n\n## 总体评价\n\n该智能体系统在 34 个真实世界任务上的综合得分为 **43.4/100**。\n\n## 维度得分\n\n| 维度 | 得分 |\n|------|------|\n| 模型构建 (Formulation) | 28.7 |\n| 正确性与一致性 (Correctness) | 39.5 |\n| 鲁棒性与验证 (Robustness) | 24.4 |\n| 分析能力 (Analysis) | 35.8 |\n\n## 各任务得分详情\n\n| Task | Score |\n|----... |
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