Understanding Calibration and Truncation Error Propagation in Training-Free Low-Rank Compression for LLMs
This work proposes a simple, training-free methodology compatible with existing frameworks to mitigate residual errors in calibration data activations accumulate across layers during compression, causing misalignment between representations simulated at compression time and those experienced at inference.