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.
ArXiv preprint, abs/2508.03905
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UNVERDICTED 3representative citing papers
DITTO uses RL with verbal feedback to train LLMs for human behavior simulation, reporting 36% average gains over base models and outperforming GPT-5.4 on 6 of 10 SOUL benchmark tasks.
SAVOIR combines prospective expected utility valuation with Shapley values for fair credit assignment in social dialogue RL, achieving SOTA on SOTOPIA where a 7B model matches or exceeds GPT-4o and Claude-3.5-Sonnet.
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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Reinforcing Human Behavior Simulation via Verbal Feedback
DITTO uses RL with verbal feedback to train LLMs for human behavior simulation, reporting 36% average gains over base models and outperforming GPT-5.4 on 6 of 10 SOUL benchmark tasks.
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SAVOIR: Learning Social Savoir-Faire via Shapley-based Reward Attribution
SAVOIR combines prospective expected utility valuation with Shapley values for fair credit assignment in social dialogue RL, achieving SOTA on SOTOPIA where a 7B model matches or exceeds GPT-4o and Claude-3.5-Sonnet.