Papers with D2D disentangles decay factor

1 papers
Disentangle to Decay: Linear Attention with Trainable Decay Factor (2025.coling-main)

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Challenge: Existing linear attention models use a decay factor based positional encoding (PE), but the decay factor is manually designed and non-trainable, limiting further optimization.
Approach: They propose a PE-based positional encoding that disentangles decay factor into two parts to achieve further optimization and stable training.
Outcome: The proposed model achieves stable training of decay factor and improves inference efficiency in normal context and extrapolation scenarios.

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