CARVQ: Corrective Adaptor with Group Residual Vector Quantization for LLM Embedding Compression

Dayin Gou, Sanghyun Byun, Nilesh Malpeddi +4

Large Language Models (LLMs) typically rely on a large number of parameters for token embedding, leading to substantial storage requirements and memory footprints. In particular, L…