Before revision:  Using case studies, we illustrate the types of insights the Embedding Comparator reveals including how fine-tuning embeddings changes semantics, how language changes over time, and how training data differences affect two seemingly similar models  .
After revision:  Using case studies, we demonstrate our system rapidly reveals insights, such as semantic changes following fine-tuning, language changes over time, and how training data differences affect two seemingly similar models .