Before revision:  We argue that such embeddings carry inadequate semantic signals . They could make the data utilization inefficient and slow down the pre-training of the entire model.
After revision:  We argue that such embeddings carry inadequate semantic signals , which could make the data utilization inefficient and slow down the pre-training of the entire model.