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English: The Transformer-XL architecture is an approach to handle long-term dependencies in sequence data. It extends the traditional Transformer model by introducing a recurrence mechanism and relative positional encoding scheme, allowing it to model longer-term dependencies more effectively. This makes it particularly useful for tasks like language modeling, where understanding the context from earlier parts of the text can be crucial for generating accurate predictions.