Files
agent/papers/items/2026-2607-04394-mechmath-agent-team-llm-driven-agents-for-mathematical-research.md
T
2026-07-08 12:25:30 +08:00

64 lines
1.4 KiB
Markdown

# Paper: MechMath Agent Team: LLM Driven Agents for Mathematical Research
---
type: paper
title: "MechMath Agent Team: LLM Driven Agents for Mathematical Research"
authors: Yichuan Cao, Ruichen Qiu, Junqi Liu, Jiaqi Wang, Dakai Guo, Ruyong Feng, Lihong Zhi, Xiao-Shan Gao
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2607.04394
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2026-07-05
updated_at: 2026-07-05
status: queued
relevance: high
topics:
- agent-evaluation
- multi-agent
- planning
- rag
- reasoning
methods:
-
benchmarks:
-
models:
-
datasets:
- cs.AI
- cs.SC
related_concepts:
-
related_jobs:
-
related_experiments:
-
related_projects:
-
collection_score: 13
collection_queries: multi-agent-llm
---
## One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
## Why Collected
- matched queries: multi-agent-llm
- inferred topics: agent-evaluation, multi-agent, planning, rag, reasoning
- arXiv categories: cs.AI, cs.SC
- collection score: 13
## Review Checklist
- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
- Does it include a benchmark, dataset, code, or reproducible experimental setup?
- Should it be promoted from `queued` to `skimmed` or `summarized`?
## Links
- arXiv: https://arxiv.org/abs/2607.04394