Abstract: To implement deep learning models on edge devices, model compression methods have been widely recognized as useful. However, it remains unclear which model compression methods are effective ...

Large Language Models (LLMs) have significantly advanced due to the Transformer architecture, with recent models like Gemini-Pro1.5, Claude-3, GPT4, and Llama3.1 demonstrating capabilities to process ...

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The rapid advancement of large language models (LLMs) has exposed critical infrastructure challenges in model deployment and communication. As models scale in size and complexity, they encounter ...

Abstract: Short texts cannot be compressed effectively with general-purpose compression methods. Methods developed to compress short texts often use static dictionaries. In order to achieve high ...