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This paper analyzes the effectiveness of decoder-only language models versus the traditional encoder-decoder architecture in sequence-to-sequence tasks. It identifies the attention degeneration problem in decoder-only models and proposes a Regularized Encoder-Decoder (RED) framework to facilitate comparison and understanding of model behaviors. The authors introduce a novel Partial Attention Language Model (PALM) to address the identified issues, supported by experimental results demonstrating its effective

Author

M

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EN