RESEARCH PAPERYear 2022

LoRA: Low-Rank Adaptation of Large Language Models

Edward J. Hu; Yelong Shen; Phillip Wallis; Zeyuan Allen-Zhu; Yuanzhi Li; Shean Wang; Lu Wang; Weizhu Chen

Classification

Major category: Foundational work
Quadrant: Not applicable
Architecture: Not applicable
Prediction paradigm: Not applicable
Subcategories: Training optimization & distillation
Source review status: Verified from primary sources

Category review. LoRA is a pre-2026 general parameter-efficient adaptation method: low-rank updates modify a frozen model and can merge into its weights. It is training background rather than the language/vision/world encoder or action decoder itself. Reading evidence

AT A GLANCE

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BibTeX

@inproceedings{lora,
  author       = {Edward J. Hu and
                  Yelong Shen and
                  Phillip Wallis and
                  Zeyuan Allen{-}Zhu and
                  Yuanzhi Li and
                  Shean Wang and
                  Lu Wang and
                  Weizhu Chen},
  title        = {LoRA: Low-Rank Adaptation of Large Language Models},
  booktitle    = {ICLR},
  year         = {2022},

}

Classification

Contribution

Abstract

Affiliations

BibTeX

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