MultiHedge combines retrieval-augmented LLMs with canonical option strategies to produce more robust allocation decisions in U.S. equities than rule-based or scale-only baselines.
In: Recent Challenges in Intelligent Information and Database Systems
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Structured reasoning artifacts enable coordination in LLM multi-agent systems by preventing approval and welfare collapse under asymmetric information while keeping bad-approval rates low across audit regimes.
citing papers explorer
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MultiHedge: Adaptive Coordination via Retrieval-Augmented Control
MultiHedge combines retrieval-augmented LLMs with canonical option strategies to produce more robust allocation decisions in U.S. equities than rule-based or scale-only baselines.
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Toward Explanatory Equilibrium: Verifiable Reasoning as a Coordination Mechanism under Asymmetric Information
Structured reasoning artifacts enable coordination in LLM multi-agent systems by preventing approval and welfare collapse under asymmetric information while keeping bad-approval rates low across audit regimes.