👉 In computational linguistics and machine learning, the concept of "katagenesis" refers to a process where a language model learns from its training data by generating new sentences based on previous ones. This approach is often used in natural language processing tasks such as text classification, sentiment analysis, and question answering. Katagenesis can be achieved through various techniques such as reinforcement learning, deep learning algorithms, or transfer learning from existing models.
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