How to Evaluate Generative AI - Approach and Metrics

Evaluating generative AI for vision (GenAI vision) is an evolving field. Human Evaluation and automatic evaluation are 2 primary ways. Technical metrics used are BLEU, GLEU, Rouge Score etc. automatical evaluation can use these. Human evaluation can be on technical metrics or broad range of task genAI do.


GENAI EVALUATION METHODS	METRIC FOR GENAI TASK	METRIC FOR EACH RESPONSE	TECHNICAL METRICS FOR GENAI

How to evaluate Generative Model

Evaluating generative model is hard

Use Human evaluation to determine quality of generated data

Inception score is used to measure quality of generated images. FID is also a measure to determine distance

KSD is way to measure distance between 2 probability distribution

BLEU score an dPerplexity is used to measure quality of generated text specially in translation.

There are diversity score to measure how diver the generated data is

The future of creativity is generative ai. Here are slides and deep dive for Generative AI

Evaluation-metrics Evaluation Genai-evaluation-methods Image-generation Implementation Metric-for-each-response Metric-for-genai-task Technical-metrics-for-genai Technical-metrics-text Test-article