arXiv cs.AI
· Papers
When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models
arXiv:2512.18934v2 Announce Type: replace-cross Abstract: Catastrophic forgetting poses a fundamental challenge in continual learning, particularly when models are quantized for deployment efficiency. We systematically investigate the interplay between quantization precision (FP16, INT8, INT4) and replay buffer strateg