% Key papers for Low-rank adaptation variants (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2024_accurate_45145,
  title = {{Accurate LoRA-Finetuning Quantization of LLMs via Information Retention}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33307},
}

@inproceedings{neurips2024_hydralora_74013,
  title = {{HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93507},
}

@inproceedings{iclr2024_qa_34612,
  title = {{QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18462},
}

@inproceedings{iclr2024_loftq_34232,
  title = {{LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18843},
}

@inproceedings{neurips2024_efficient_71445,
  title = {{Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95811},
}

@inproceedings{cvpr2025_lora_26805,
  title = {{LoRA Recycle: Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAs}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34696},
}

@inproceedings{neurips2025_gora_78289,
  title = {{GoRA: Gradient-driven Adaptive Low Rank Adaptation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=d1dL1ymD6N},
}

@inproceedings{iclr2024_bayesian_34004,
  title = {{Bayesian Low-rank Adaptation for Large Language Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19071},
}

@inproceedings{neurips2024_prompt_72280,
  title = {{Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95065},
}

@inproceedings{neurips2025_activated_77268,
  title = {{Activated LoRA: Fine-tuned LLMs for Intrinsics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=S6SKa97Gm0},
}

@inproceedings{neurips2025_all_77691,
  title = {{All You Need is One: Capsule Prompt Tuning with a Single Vector}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=WZS7sJiSUm},
}

@inproceedings{iclr2025_salora_81493,
  title = {{SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30283},
}

@inproceedings{icml2024_bbox_45159,
  title = {{BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33293},
}

@inproceedings{icml2025_compress_46016,
  title = {{Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46530},
}

@inproceedings{icml2025_lowra_46700,
  title = {{LowRA: Accurate and Efficient LoRA Fine-Tuning of LLMs under 2 Bits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45872},
}

@inproceedings{icml2025_joint_47012,
  title = {{Joint Localization and Activation Editing for Low-Resource Fine-Tuning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45572},
}

@inproceedings{icml2025_make_47371,
  title = {{Make LoRA Great Again: Boosting LoRA with Adaptive Singular Values and Mixture-of-Experts Optimization Alignment}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45221},
}

@inproceedings{icml2025_lora_48567,
  title = {{LoRA-Gen: Specializing Large Language Model via Online LoRA Generation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44054},
}

@inproceedings{icml2026_a_51173,
  title = {{A Language-Guided Bayesian Optimization for Efficient LoRA Hyperparameter Search}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=JNdi6E05NJ},
}

@inproceedings{icml2026_geometry_52645,
  title = {{Geometry-Preserving Orthonormal Initialization for Low-Rank Adaptation in RLVR}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Xo95FS2GTK},
}