Security-Enhanced Seed-Based Weight Quantization for Large Language Models
Large language models (LLMs) incur substantial storage, memory-bandwidth and energy costs, motivating compact weight representations. Existing seed-based compression methods reconstruct weights from compact pseudo-random representations but do not explicitly account for the non-uniform sensitivity of model weights. We...
Qiu-Yu Ren, Sudipta Paria, Aritra Dasgupta et al.
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