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It is suggested that fully patient-independent neonatal seizure prediction remains challenging, but that patient-adaptive fine-tuning with a small amount of data may provide a practical pathway toward personalized neonatal seizure prediction systems.
The key-value (KV) cache has become the dominant consumer of memory in large language model (LLM) serving systems as context lengths, concurrency, and request lifetimes grow. High-bandwidth memory (HBM) provides the bandwidth attention decode needs but limited capacity, while off-package memory and storage add capacity...
Experimental results indicate that such complex designs exceed the capabilities of existing approaches, whereas the proposed LLM-based hardware development framework is the only one capable of producing functional end-to-end design.
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