Multi-Stream Attention Residuals (MSAR) extends the AttnRes method by generalizing the attention mechanism to multi-head depth, achieving significant performance improvements with minimal additional overhead. MSAR leverages multi-scale causal convolutions to draw stream diversity from sequence context, allowing different heads to retrieve historical representations through distinct contextual views.
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MSAR can be useful for large-scale pre-training as it offers improved performance with low additional overhead.
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