A new benchmark called Riemann-Bench has been introduced to evaluate AI systems on advanced, research-level mathematics, moving beyond the scope of competition problems. Developed by Ivy League mathematics professors and experts, the benchmark features problems that are complex and time-consuming to solve, even for humans. Initial evaluations show that current frontier AI models score below 10% on Riemann-Bench, highlighting a significant gap in their mathematical reasoning capabilities compared to human researchers. The benchmark is kept private to prevent data memorization and ensure a true assessment of AI's mathematical prowess. AI
IMPACT Reveals a significant gap in AI's ability to perform advanced mathematical reasoning, suggesting current models are far from research-level capabilities.
RANK_REASON The cluster describes a new benchmark for AI research published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
- alphaXiv
- arXiv
- CatalyzeX
- DagsHub
- Gotit.pub
- Hugging Face
- International Mathematical Olympiad
- Ivy League
- Riemann-Bench
- ScienceCast
- Sushant Mehta
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