👉 Score computing is a method used to quantify the quality or relevance of text generated by AI models, such as language generators. It involves calculating a numerical score based on how well the generated text matches a given reference or target text, often using predefined metrics like BLEU (Bilingual Evaluation Understudy), ROUGE (Recall-Oriented Understudy for Gisting Evaluation), or METEOR (Metric for Evaluation of Translation with Explicit ORdering). These metrics assess aspects like precision, recall, and coherence, providing a score that reflects the model's performance. Higher scores indicate better alignment with the desired output, enabling users to evaluate and compare different AI-generated texts efficiently.
