This study revisits the issue of pruning large language models (LLMs), particularly from the BERT family, in response to the Sparsity May Cry (SMC) benchmark. The benchmark highlights the complexity…
Continue readingThe article discusses the efficiency of black-box prompt search in large language models (LLMs). The authors highlight the importance of search space design and optimization, which has often been overlooked…
Continue readingThe study discusses the use of neural network pruning as an effective method for compressing a multilingual ASR model with minimal performance loss. The proposed adaptive masking approach results in…
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