June 7, 2024, 4:52 a.m. | Junmo Kang, Hongyin Luo, Yada Zhu, Jacob Hansen, James Glass, David Cox, Alan Ritter, Rogerio Feris, Leonid Karlinsky

cs.CL updates on arXiv.org arxiv.org

arXiv:2310.00160v2 Announce Type: replace
Abstract: Recent works have demonstrated the effectiveness of self-alignment in which a large language model is aligned to follow general instructions using instructional data generated from the model itself starting from a handful of human-written seeds. Instead of general alignment, in this work, we focus on self-alignment for expert domain specialization (e.g., biomedicine, finance). As a preliminary, we quantitively show the marginal effect that generic instruction-following training has on downstream expert domains' performance. To remedy this, …

abstract alignment arxiv cs.ai cs.cl data expertise focus general generated human language language model language models large language large language model large language models replace type work

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