Self-attention mechanisms and transformer architectures, proposed in the late 2010s, revolutionized sequence modeling for natural language processing by allowing models to focus on different parts of the input sequence when generating output.

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  The Synergy of Symbolic and Connectionist AI in LLM-Empowered ...

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• The Synergy of Symbolic and Connectionist AI in LLM-Empowered ... arxiv.org arXiv via serper
• The Synergy of Symbolic and Connectionist AI in LLM ... arxiv.org arXiv via serper

Referenced by nodes (2)

• natural language processing concept
• self-attention mechanism concept