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Found 3 papers, 2 papers with code
Explore, Select, Derive, and Recall: Augmenting LLM with Human-like Memory for Mobile Task Automation
The advent of large language models (LLMs) has opened up new opportunities in the field of mobile task automation.
Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models
As a result, K-prune shows significant accuracy improvements up to 58. 02%p higher F1 score compared to existing retraining-free pruning algorithms under a high compression rate of 80% on the SQuAD benchmark without any retraining process.
A Queueing Model of Patient Flow for Stroke Networks to Estimate Acute Stroke Transfer Capacity
Data simulations of the model, using a base case and an expanded case, were performed to illustrate the effects of changing key parameters, such as transfer rates from PSCs and CSC Neuro-ICU capacity on overflow capacity.
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