D-QRELO compresses LLM delta weights via one-bit quantization followed by compensated residual low-rank approximation and outperforms prior methods on dense and MoE models with large SFT datasets.
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D-QRELO: Training- and Data-Free Delta Compression for Large Language Models via Quantization and Residual Low-Rank Approximation
D-QRELO compresses LLM delta weights via one-bit quantization followed by compensated residual low-rank approximation and outperforms prior methods on dense and MoE models with large SFT datasets.