Abstract: Natural Language Processing (NLP) has achieved significant success in complex tasks across various domains, yet it also brings high computational costs and inference delays. Pruning, as a ...
As the use of generative AI becomes increasingly common, we must beware of an algorithmic colonization of language and ...
Abstract: Large language models have shown impressive capabilities in natural language processing tasks, but their deployment is hindered by high computational costs and lack of domain specificity.
AI's value depends on the educators and leaders who wield it with intention and a commitment to equity, fairness, responsibility, and balance.
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