Overview
MMLU-Pro, developed by the TIGER AI Lab, represents a significant enhancement to the original MMLU benchmark. It increases difficulty, expands coverage, and introduces more challenging questions designed to better differentiate between AI models.
Key Improvements Over Original MMLU
| Feature | MMLU (Original) | MMLU-Pro |
|---|---|---|
| Total Questions | ~10,000 | 12,000+ |
| Answer Options | 4 | 10 |
| Difficulty Level | Undergraduate | Graduate-level |
| Reasoning Depth | Moderate | Deeper required |
Subject Coverage
MMLU-Pro covers 14 major academic subject areas:
| Category | Subjects |
|---|---|
| STEM | Physics, chemistry, biology, mathematics |
| Humanities | History, philosophy, law |
| Social Sciences | Psychology, sociology, economics |
| Professional | Medicine, engineering, computer science |
| Other | Business, ethics, political science |
Why Graduate-Level?
Graduate-level questions in MMLU-Pro require:
- Deeper understanding of fundamental concepts
- Integration of knowledge across multiple domains
- Critical thinking and analysis
- Application of theoretical knowledge to practical scenarios
- Nuanced understanding rather than surface-level recall
Answer Format
With 10 answer options (compared to 4 in original MMLU), guessing becomes much more difficult, making the benchmark more reliable for measuring true knowledge.
Purpose
MMLU-Pro provides a rigorous test of AI models’ academic capabilities, specifically designed to:
- Challenge even the most capable AI systems
- Better differentiate between model capabilities
- Reflect real-world graduate-level expertise requirements
- Provide stable, reproducible evaluation metrics
Source: TIGER AI Lab
