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näkemys - Memory-Augmented Transformers for Conversational AI
Memory-Augmented Generative Adversarial Transformers: Enhancing Conversational AI Systems with External Data
The author proposes memory-augmented Generative Adversarial Transformers to enhance conversational AI systems by incorporating external data. This approach aims to improve factual question-answering and style adaptation in dialogues.
Memory-Augmented Generative Adversarial Transformers: Enhancing Conversational AI Systems with External Data
Erweiterung von Transformers mit externem Wissen verbessert die Leistung für Faktenbeantwortung und Stilanpassung.
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