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PhaseQuant: Mitigating Activation Quantization Collapse via Residual-Stream Dynamics
Post-training quantization (PTQ) is essential for efficient large language model (LLM) inference, but reliably quantizing activations remains challenging when weights, activations, and KV caches are all quantized to 4-bit precision. A key difficulty lies in massive activations, whose extreme values
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