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Architectural choices in multi-agent systems can fundamentally shape their alignment with human values, offering a blueprint for trustworthy AI deployment.
VADAOrchestra achieves verifiable and adaptable decision-making workflows by seamlessly integrating LLMs with symbolic reasoning, outperforming traditional systems in real-world applications.
Recurrent models can achieve competitive text embedding performance with constant memory usage, challenging the dominance of transformers in long-sequence tasks.
