arXiv (All)
open access
GTA: Graph Theory Agent and Benchmark for Algorithmic Graph Reasoning with LLMs
Large Language Models (LLMs) are increasingly asked to reason over structured data such as graphs, yet how reliably they can carry out multi-step graph algorithms in language remains unclear. Existing evaluations tend to use simple tasks on small graphs, to score code generation rather than reasonin
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- DARE: Dialectical Agentic Reasoning for Structured Knowledge Fact Checking#1083306
- Hypergraph Enterprise Agentic Reasoner over Heterogeneous Business Systems#984157
- GraphMAS: A Systematic Benchmark of Multi-Agent Coordination for Graph Learning#1144944
- Cogentic: Multi-Agent Orchestration for Automated Proof Discovery#1154584
- Cogentic: Multi-Agent Orchestration for Automated Proof Discovery#1136858
Record · ID 1000225
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive