<?xml version="1.0" encoding="UTF-8"?><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>lora-low-rank-adaptation-of-large-language-models-2026-012</dc:title><dc:creator>Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen</dc:creator><dc:date>2026</dc:date><dc:description>This record links to the LoRA paper, which introduces low-rank adaptation for efficient fine-tuning of large language models. It is useful for testing AI thesis metadata, modern NLP keywords, and external PDF access.</dc:description><dc:identifier>https://inrepscholar.com/projects/951</dc:identifier></oai_dc:dc>