Data Distillation Meets Prompt Compression: How Tsinghua University and Microsoft’s LLMLingua-2 Is Redefining Efficiency in Large Language Models Using Task-Agnostic Techniques

In a collaborative effort that underscores the importance of interdisciplinary research, Tsinghua University and Microsoft Corporation researchers have unveiled LLMLingua-2. This groundbreaking study delves into language model efficiency, aiming to streamline communication between humans and machines and reduce the verbosity of natural language without compromising the conveyed information’s essence. The central challenge of this endeavor […]

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