Graphia is an LLM post-training framework that uses real social graphs and GNN rewards to improve micro-level interaction prediction and macro-level network property replication in dynamic social simulations.
CoRR, abs/2504.00711
2 Pith papers cite this work. Polarity classification is still indexing.
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LAGA is a unified multi-agent LLM framework that automates comprehensive quality optimization for text-attributed graphs by running detection, planning, action, and evaluation agents in a closed loop.
citing papers explorer
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GRAPHIA: Harnessing Social Graph Data to Enhance LLM-Based Social Simulation
Graphia is an LLM post-training framework that uses real social graphs and GNN rewards to improve micro-level interaction prediction and macro-level network property replication in dynamic social simulations.
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When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach
LAGA is a unified multi-agent LLM framework that automates comprehensive quality optimization for text-attributed graphs by running detection, planning, action, and evaluation agents in a closed loop.