Randomized Weibull anchors and debiased collective memory with decay and inflection bonuses let agentic AI in 6G cut anchoring, temporal, and confirmation biases, doubling energy savings to 25% and reducing latency by 5x in simulations.
End-to-end edge ai service provisioning framework in 6g oran
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LLM agents for 6G slicing exhibit anchoring bias mitigated by Truncated Weibull randomization plus CVaR digital twins, yielding up to 25% energy savings and sub-second inference on a 1B model.
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A Tutorial on Cognitive Biases in Agentic AI-Driven 6G Autonomous Networks
Randomized Weibull anchors and debiased collective memory with decay and inflection bonuses let agentic AI in 6G cut anchoring, temporal, and confirmation biases, doubling energy savings to 25% and reducing latency by 5x in simulations.
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Mitigating Anchoring Bias in LLM-Based Agents for Energy-Efficient 6G Autonomous Networks
LLM agents for 6G slicing exhibit anchoring bias mitigated by Truncated Weibull randomization plus CVaR digital twins, yielding up to 25% energy savings and sub-second inference on a 1B model.