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About this paper
Mukund Athmaram, Manoj Rao, Liang Ma
The authors present an on-device language-model runtime that schedules weight precision as conversation context grows. It measures tensor sensitivity and execution costs, then switches weight versions while retaining the KV cache. On a 4K-context WikiText evaluation, its cost-calibrated schedule reduced joint KL by 16.8% and mean decode latency by 3.3% versus byte-aware scheduling; the evidence is a laptop-GPU demonstration.
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