AI × CryptoNeutralarXiv – CS AI · Jun 17/10
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Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution
Researchers evaluated multi-agent LLM architectures for resolving prediction market outcomes, finding that independent aggregation with confidence-weighted voting achieves 83.43% accuracy—marginally better than single models. Deliberative consensus between agents actually degraded performance, while high error correlations across models (0.529-0.689) limit ensemble gains, suggesting hybrid AI-human systems with strategic escalation criteria offer the most practical path forward.
🧠 GPT-5🧠 Llama