Memory Augmented Network is a neural architecture that integrates external memory with standard models to enhance reasoning and recall. NEC Labs America explores memory augmented networks for tasks requiring long-term dependencies, such as multimodal analytics and biomedical text mining. These networks improve interpretability and extend problem-solving capabilities, making them valuable tools in real-world applications where context retention is critical.

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Dual Privacy Protection for Distributed Fiber Sensing with Disaggregated Inference and Fine-tuning of Memory-Augmented Networks

We propose a memory-augmented model architecture with disaggregated computation infrastructure for fiber sensing event recognition. By leveraging geo-distributed computingresources in optical networks, this approach empowers end-users to customize models while ensuring dual privacy protection.