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cs.LG2025
DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory
Jerry Chee, Arturs Backurs, Rainie Heck +4
Quantizing the weights of a neural network has two steps: (1) Finding a good low bit-complexity representation for weights (which we call the quantization grid) and (2) Rounding th…
cs.LG2024
QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks
Albert Tseng, Jerry Chee, Qingyao Sun +2
Post-training quantization (PTQ) reduces the memory footprint of LLMs by quantizing their weights to low-precision. In this work, we introduce QuIP#, a weight-only PTQ method that…