CAIRN: Dynamic Fact-Intent DAGs for Multi-Agent Exploration

arXiv:2609.32700 · cs.AI · Submitted 2026-09-26 · Read on arXiv

cs.AI

Submitted: 2026-09-26

Updated: 2026-09-26

Code: https://github.com/openai/plugins

Project page: https://tsecbench.zc.tencent.com

Terminology

• Benchmark — 29× in this paper · explained in 2 episodes
• Verification — 16× in this paper · explained in 2 episodes
• Trace — 5× in this paper · explained in 2 episodes
• Multi-Agent System — 3× in this paper · explained in 6 episodes
• Verifier — 3× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Agentic AI — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• Hypergraph — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Multi-agent Collaboration — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes

Sources

• Every Model Cheats: Prompt-Level Mitigation of Cheating on Offensive Cyber Tasks
• How Inference Compute Shapes Frontier LLM Evaluation
• D-CIPHER: Dynamic Collaborative Intelligent Multi-Agent System with Planner and Heterogeneous Executors for Offensive Security
• AI co-mathematician: Accelerating mathematicians with agentic AI

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