Long-Context Bottlenecks: Synthetic Data Trumps Attention Mechanisms
SkyLi0n · x · 2026-07-11
Addressing whether specific efficient attention mechanisms truly matter, the author notes that cutting-edge models use various effective variants, making them difficult to compare horizontally.
They emphasize that in long-context model training, synthetic mid-training data is often an equal or even greater bottleneck.
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