LLM interprets natural-language policies to steer a projected-gradient power allocator in 8 parallel QPSK-AWGN channels, producing policy-dependent allocations and 60% lower mutual-information spread after abrupt channel reversals compared with the optimizer alone.
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PolySwarm aggregates predictions from 50 LLM personas for Polymarket trading using Bayesian combination and divergence metrics, outperforming single models in calibration while adding latency arbitrage via CEX price models.
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LLM-Steered Power Allocation for Parallel QPSK-AWGN Channels
LLM interprets natural-language policies to steer a projected-gradient power allocator in 8 parallel QPSK-AWGN channels, producing policy-dependent allocations and 60% lower mutual-information spread after abrupt channel reversals compared with the optimizer alone.
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PolySwarm: A Multi-Agent Large Language Model Framework for Prediction Market Trading and Latency Arbitrage
PolySwarm aggregates predictions from 50 LLM personas for Polymarket trading using Bayesian combination and divergence metrics, outperforming single models in calibration while adding latency arbitrage via CEX price models.