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DeepMath: A lightweight math reasoning Agent with smolagents
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Jul 5
MechMath Agent Team: LLM Driven Agents for Mathematical Research
AI reasoning has become a central focus in contemporary artificial intelligence, largely driven by the success of large language models. However, mathematical research, which is characterized by non-linear derivation paths, rigorous logical requirements, and protracted exploration cycles, poses severe challenges for existing reasoning systems.
arXiv AI
Jul 7
MechMath Agent Team: LLM Driven Agents for Mathematical Research
arXiv:2607. 04394v1 Announce Type: new Abstract: AI reasoning has become a central focus in contemporary artificial intelligence, largely driven by the success of large language models.
arXiv AI
Jul 8
Mathematical Reasoning in Large Language Models: Benchmarks, Architectures, Evaluation, and Open Challenges
arXiv:2605. 19723v2 Announce Type: replace-cross Abstract: Mathematical reasoning is essential for problem-solving in education, science, and industry, serving as a crucial benchmark for evaluating artificial intelligence systems.
arXiv AI
Jun 19
SIGMA: Search-Augmented On-Demand Knowledge Integration for Agentic Mathematical Reasoning
arXiv:2510. 27568v2 Announce Type: replace Abstract: Solving mathematical reasoning problems requires not only accurate access to relevant knowledge but also careful, multi-step thinking.
arXiv AI
Sep 3
AI Mathematician: Towards Fully Automated Frontier Mathematical Research
The paper introduces the AI Mathematician (AIM) framework, which leverages Large Reasoning Models (LRMs) to tackle frontier mathematical research. AIM addresses the complexity and procedural rigor of research problems through an exploration mechanism for longer solution paths and a pessimistic reasonable verification method for reliability. Early experiments show AIM can autonomously construct significant proof components and uncover non‑trivial insights across real‑world mathematical topics.
arXiv AI
Jul 9
Evaluating SageMath-Augmented LLM Agents for Computational and Experimental Mathematics
arXiv:2607. 06820v1 Announce Type: new Abstract: Recent advances in AI for Mathematics have focused largely on autoformalization and theorem proving, leaving the role of Computer Algebra Systems (CAS) in agentic LLM workflows underexplored.