% Key papers for Efficient LLM fine-tuning systems (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2020_language_60135,
  title = {{Language Models are Few-Shot Learners}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18544},
}

@inproceedings{aaai2020_fine_102979,
  title = {{Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6289},
}

@inproceedings{iclr2024_longlora_33685,
  title = {{LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19390},
}

@inproceedings{aaai2020_learning_103211,
  title = {{Learning to Compare for Better Training and Evaluation of Open Domain Natural Language Generation Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6521},
}

@inproceedings{aaai2024_fine_6023,
  title = {{Fine-Tuning Large Language Model Based Explainable Recommendation with Explainable Quality Reward}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28777},
}

@inproceedings{iclr2024_a_34892,
  title = {{A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18182},
}

@inproceedings{cvpr2024_ltgc_23907,
  title = {{LTGC: Long-tail Recognition via Leveraging LLMs-driven Generated Content}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30666},
}

@inproceedings{neurips2023_to_67177,
  title = {{To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72533},
}

@inproceedings{icml2024_contrastive_43458,
  title = {{Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34994},
}

@inproceedings{iclr2024_yarn_35574,
  title = {{YaRN: Efficient Context Window Extension of Large Language Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17499},
}

@inproceedings{iclr2025_judgelm_84066,
  title = {{JudgeLM: Fine-tuned Large Language Models are Scalable Judges}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27760},
}

@inproceedings{iclr2024_octopack_35198,
  title = {{OctoPack: Instruction Tuning Code Large Language Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17875},
}

@inproceedings{neurips2023_distributed_68486,
  title = {{Distributed Inference and Fine-tuning of Large Language Models Over The Internet}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71336},
}

@inproceedings{neurips2025_large_76573,
  title = {{Large Language Diffusion Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=KnqiC0znVF},
}

@inproceedings{aaai2022_on_2499,
  title = {{On the Transferability of Pre-trained Language Models: A Study from Artificial Datasets}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/10518-on-the-transferability-of-pre-trained-language-models-a-study-from-artificial-datasets/},
}

@inproceedings{icml2024_language_44999,
  title = {{Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33453},
}

@inproceedings{icml2024_llm_45345,
  title = {{LLM Maybe LongLM: SelfExtend LLM Context Window Without Tuning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33106},
}

@inproceedings{neurips2023_language_66815,
  title = {{Language Models are Weak Learners}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72822},
}

@inproceedings{neurips2024_large_72525,
  title = {{Large Scale Transfer Learning for Tabular Data via Language Modeling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94842},
}

@inproceedings{icml2024_self_44273,
  title = {{Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34179},
}

@inproceedings{neurips2024_blob_71786,
  title = {{BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95507},
}

@inproceedings{icml2024_revisiting_44473,
  title = {{Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33979},
}

@inproceedings{neurips2024_smalltolarge_71592,
  title = {{SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95679},
}

@inproceedings{neurips2024_customizing_73486,
  title = {{Customizing Language Models with Instance-wise LoRA for Sequential Recommendation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93987},
}

@inproceedings{neurips2024_retrieval_70319,
  title = {{Retrieval \& Fine-Tuning for In-Context Tabular Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96776},
}

@inproceedings{iclr2025_generative_84111,
  title = {{Generative Monoculture in Large Language Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27717},
}

@inproceedings{iclr2024_dynamic_33503,
  title = {{Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19572},
}