Looped language model training cannot control hidden-state norm growth because RMSNorm normalizes scale away before the loss ...
NVIDIA diffusion language model Nemotron TwoTower achieves 2.42x LLM inference throughput without a full retraining run, ...
Because this happens every generated token, indexer-score and top-k kernels are part of TPOT, not just setup overhead. M3's sparse-attention config controls block size, top-k count, optional init ...
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