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ROUGE

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What is ROUGE Metrics – Recall-Oriented Understudy for Gisting Evaluation?

2025-07-08T11:24:28+00:00

Recall-Oriented Understudy for Gisting Evaluation (ROUGE) Cheat Sheet ROUGE is a family of metrics designed to assess the similarity between machine-generated text (candidate) and human-written reference text (ground truth) in NLP tasks like text summarization and machine translation. Measures how well generated text captures key information and structure from reference text, emphasizing recall (proportion of relevant information preserved). Score Range: 0 to 1, where higher scores indicate greater similarity between candidate and reference texts. Key Use Cases: Evaluating text summarization systems. Assessing machine translation quality. Analyzing content accuracy in generated text. Types of ROUGE Metrics ROUGE-N: Measures the overlap of [...]

What is ROUGE Metrics – Recall-Oriented Understudy for Gisting Evaluation?2025-07-08T11:24:28+00:00

Methods in Evaluating Foundation Model Performance

2024-11-29T05:59:36+00:00

A foundation model is a large-scale, pre-trained artificial intelligence model that serves as a general-purpose system for various downstream tasks. These models, such as GPT for natural language processing or CLIP for vision-language understanding, are trained on extensive datasets and can be fine-tuned or adapted to specific applications. Foundation models are characterized by their ability to generalize across tasks, making them highly versatile and impactful in AI-driven solutions. Evaluating these models' performance is essential to understand their reliability, applicability, and potential business value. However, these models' vast scale and complexity pose unique challenges for evaluation, requiring a multifaceted approach. This article [...]

Methods in Evaluating Foundation Model Performance2024-11-29T05:59:36+00:00

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