June 10, 2024, 4:41 a.m. | Wei Pang, Chuan Zhou, Xiao-Hua Zhou, Xiaojie Wang

cs.CL updates on arXiv.org arxiv.org

arXiv:2406.04371v1 Announce Type: new
Abstract: Instruction Fine-Tuning, a method enhancing pre-trained language models' capabilities from mere next-word prediction to complex instruction following, often employs a one-off training approach on diverse instruction dataset. However, this method may not effectively enhance models' adherence to instructions due to the simultaneous handling of varying instruction complexities. To address this, we propose a novel phased instruction fine-tuning (Phased IFT) method, grounded in the hypothesis of progressive alignment, which posits that the transition of a pre-trained …

arxiv cs.ai cs.cl fine-tuning language language models large language large language models type

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