Параметрически Эффективная Тонкая Настройка

AbstractParameter-efficient fine-tuning (PEFT) of pre-trained language models has recently demonstrated remarkable achievements, effectively matching the performance of full fine-tuning while utilizing significantly fewer trainable parameters, and consequently addressing the storage …...

AbstractA fundamental challenge in the current NLP context, dominated by language models, comes from the inflexibility of current architectures to “learn” new information. While model-centric solutions like continual learning or …...