QSLM automates tiered quantization of spike-driven language models via sensitivity analysis and multi-objective search, delivering up to 86.5% memory reduction and 20% power savings while keeping accuracy close to the full-precision baseline.
Embodied neuromorphic intelligence
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
A neuromorphic spiking ring attractor maintains stable multi-second representations of robot joint angles with reduced drift near limits and a near-linear velocity-to-bump-speed relationship.
citing papers explorer
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QSLM: A Performance- and Memory-aware Quantization Framework with Tiered Search Strategy for Spike-driven Language Models
QSLM automates tiered quantization of spike-driven language models via sensitivity analysis and multi-objective search, delivering up to 86.5% memory reduction and 20% power savings while keeping accuracy close to the full-precision baseline.
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Neuromorphic Spiking Ring Attractor for Proprioceptive Joint-State Estimation
A neuromorphic spiking ring attractor maintains stable multi-second representations of robot joint angles with reduced drift near limits and a near-linear velocity-to-bump-speed relationship.