% Key papers for LoRA variants and theory (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2024_pissa_70601,
  title = {{PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96517},
}

@inproceedings{icml2024_dora_43400,
  title = {{DoRA: Weight-Decomposed Low-Rank Adaptation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35052},
}

@inproceedings{cvpr2024_mtlora_24084,
  title = {{MTLoRA: Low-Rank Adaptation Approach for Efficient Multi-Task Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31243},
}

@inproceedings{neurips2024_lora_72474,
  title = {{LoRA-GA: Low-Rank Adaptation with Gradient Approximation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94885},
}

@inproceedings{icml2024_lora_44243,
  title = {{LoRA+: Efficient Low Rank Adaptation of Large Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34209},
}

@inproceedings{icml2024_galore_45062,
  title = {{GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33390},
}

@inproceedings{neurips2025_lora_80258,
  title = {{LoRA vs Full Fine-tuning: An Illusion of Equivalence}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=xp7B8rkh7L},
}

@inproceedings{iclr2024_vera_34300,
  title = {{VeRA: Vector-based Random Matrix Adaptation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18775},
}

@inproceedings{iclr2024_the_35150,
  title = {{The Expressive Power of Low-Rank Adaptation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17923},
}

@inproceedings{icml2024_parameter_44631,
  title = {{Parameter-Efficient Fine-Tuning with Discrete Fourier Transform}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33821},
}

@inproceedings{cvpr2025_iteris_26659,
  title = {{IterIS: Iterative Inference-Solving Alignment for LoRA Merging}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34667},
}

@inproceedings{neurips2024_sparse_70616,
  title = {{Sparse High Rank Adapters}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96503},
}

@inproceedings{neurips2024_unveiling_74360,
  title = {{Unveiling LoRA Intrinsic Ranks via Salience Analysis}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93201},
}

@inproceedings{cvpr2025_coap_25658,
  title = {{COAP: Memory-Efficient Training with Correlation-Aware Gradient Projection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35119},
}

@inproceedings{iclr2024_batched_35565,
  title = {{Batched Low-Rank Adaptation of Foundation Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17508},
}

@inproceedings{neurips2025_accurate_80275,
  title = {{Accurate and Efficient Low-Rank Model Merging in Core Space}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=y1z7SAS8q8},
}

@inproceedings{iclr2025_computational_81797,
  title = {{Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29984},
}

@inproceedings{iclr2024_nola_34518,
  title = {{NOLA: Compressing LoRA using Linear Combination of Random Basis}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18556},
}

@inproceedings{neurips2024_bridging_71732,
  title = {{Bridging The Gap between Low-rank and Orthogonal Adaptation via Householder Reflection Adaptation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95554},
}

@inproceedings{neurips2024_vb_73628,
  title = {{VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93861},
}