👉 Includes computing, also known as include generation or inclusion generation, is a process in natural language processing (NLP) where a model generates text by incorporating previously generated text segments, often referred to as "tokens" or "inclusions," into its output. This technique is commonly used in sequence-to-sequence models, where the model takes an input sequence and generates a corresponding output sequence. During computation, the model predicts the next token in the output sequence based on the context provided by the preceding tokens, and it uses previously included tokens to maintain coherence and context throughout the generated text. This allows for the creation of more coherent and contextually relevant responses, especially in tasks like summarization, dialogue generation, and machine translation.
