K. Gorgônio

Few-shot prompting boosts LLM performance in generating microservice architectures, achieving an impressive F1 score of 0.97 for service identification.

Structural evaluations of LLM-generated microservices reveal that apparent differences in prompting strategies may mask underlying methodological biases rather than true architectural quality.

The sheer breadth of IoT attack vectors, from node replication to skimming, highlights the urgent need for comprehensive security strategies that address device limitations and lack of standardization.

Differential Privacy can wreak havoc on the delicate firing rate dynamics of federated spiking neural networks, leading to instability in client selection and attenuated aggregation.