Contextual word representations are a type of word embedding that captures the meaning of words based on their context in a sentence, allowing for more nuanced understanding and disambiguation of words with multiple meanings. These representations are generated by deep learning models, such as transformers, which process entire sentences or documents to understand the relationships between words.