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New agentic system RMA solves research-level math problems

Researchers have developed RMA, an agentic system designed to tackle complex, research-level mathematical problems. This framework breaks down the proof-solving process into specialized modules for analysis, literature review, and verification, coordinated by multiple agents. RMA demonstrated superior performance on the First Proof benchmark, solving eight out of ten problems and generating more robust proofs compared to existing systems like GPT-5.2R and Aletheia. AI

Summary written by gemini-2.5-flash-lite from 1 sources. How we write summaries →

IMPACT This system could accelerate AI's ability to contribute to novel mathematical discovery and formal verification.

RANK_REASON The cluster describes a new research paper detailing an agentic system for solving mathematical problems. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

COVERAGE [1]

  1. arXiv cs.AI TIER_1 · Zelin Zhao, Bo Yuan, Jaemoo Choi, Yongxin Chen ·

    RMA: an Agentic System for Research-Level Mathematical Problems

    arXiv:2605.22875v1 Announce Type: new Abstract: We present $\textbf{Research Math Agents (RMA)}$, an agentic framework for automated reasoning on research-level mathematical problems. Unlike prior studies centered on competition mathematics or formal theorem proving, RMA targets …