Artificial Intelligence #ai#llm
Mitigating Anchoring Bias in LLM Agents Boosts Energy Efficiency in 6G Autonomous Networks
Researchers propose a randomized anchoring strategy using a Truncated Weibull distribution to mitigate anchoring bias in LLM-based agents for 6G autonomous networks. The approach achieves up to 25% energy savings and sub-second inference latency, compatible with O-RAN architecture.
Jun 21, 2026 1 source