Ji-Cather/GraphAgent
Code for ACL25-findings. An LLM-based agent simulation framework that simulates human behavior and generates dynamic, text-based social graphs.
Implements multi-agent simulation using AgentScope with configurable LLM backends (OpenAI, vLLM) to generate text-attributed temporal graphs that match real-world structural and textual properties. The framework validates generated graphs against seven macroscopic network properties and demonstrates 11% improvement in microscopic structure metrics compared to existing graph generation methods. Supports diverse domains—social media, e-commerce, and citation networks—with parallel execution via distributed launcher architecture and optional user-prompt-driven configuration for rapid environment setup.
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Last pushed
Oct 23, 2025
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