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Combining Entropy And Matrix Nuclear Norm For Enhanced Evaluation Of Language Models

James Vo·2024

Abstract

As large language models (LLMs) continue to advance, the need for precise and efficient evaluation metrics becomes more pressing. Traditional approaches, while informative, often face limitations in computational demands and interpretability. In this paper, we introduce a novel hybrid evaluation method that integrates two established techniques: entropy derived from covariance matrices and the Mat

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