Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs
arXiv:2510.18245v3 Announce Type: replace-cross
Abstract: Scaling the number of parameters and the size of training data has proven to be an effective strategy for improving large language model (LLM) performance. Yet, as these models grow increasingl…