% Key papers for State space and recurrent sequence models (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{aaai2018_disan_105881,
  title = {{DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11941},
}

@inproceedings{cvpr2017_global_12314,
  title = {{Global Context-Aware Attention LSTM Networks for 3D Action Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{icml2016_ask_35741,
  title = {{Ask Me Anything: Dynamic Memory Networks for Natural Language Processing}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/kumar16.html},
}

@inproceedings{iclr2022_efficiently_31781,
  title = {{Efficiently Modeling Long Sequences with Structured State Spaces}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6959},
}

@inproceedings{icml2021_msa_39585,
  title = {{MSA Transformer}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9905},
}

@inproceedings{aaai2019_character_101495,
  title = {{Character-Level Language Modeling with Deeper Self-Attention}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4182},
}

@inproceedings{neurips2019_deep_58095,
  title = {{Deep Equilibrium Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14487},
}

@inproceedings{icml2017_online_36327,
  title = {{Online and Linear-Time Attention by Enforcing Monotonic Alignments}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/866},
}

@inproceedings{neurips2023_hyenadna_69805,
  title = {{HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70142},
}

@inproceedings{cvpr2019_aggregation_13838,
  title = {{Aggregation Cross-Entropy for Sequence Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{iclr2023_hungry_32228,
  title = {{Hungry Hungry Hippos: Towards Language Modeling with State Space Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11738},
}

@inproceedings{neurips2017_deconvolutional_56233,
  title = {{Deconvolutional Paragraph Representation Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9197},
}

@inproceedings{cvpr2017_temporal_12687,
  title = {{Temporal Attention-Gated Model for Robust Sequence Classification}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{iclr2023_simplified_32193,
  title = {{Simplified State Space Layers for Sequence Modeling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11401},
}

@inproceedings{iclr2018_bi_28494,
  title = {{Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/234},
}

@inproceedings{iclr2018_generating_28565,
  title = {{Generating Wikipedia by Summarizing Long Sequences}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/121},
}

@inproceedings{aaai2021_dynamic_480,
  title = {{Dynamic Memory based Attention Network for Sequential Recommendation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/04384-dynamic-memory-based-attention-network-for-sequential-recommendation/},
}

@inproceedings{neurips2022_diagonal_64949,
  title = {{Diagonal State Spaces are as Effective as Structured State Spaces}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54460},
}

@inproceedings{aaai2017_coherent_105839,
  title = {{Coherent Dialogue with Attention-Based Language Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10961},
}

@inproceedings{aaai2021_classifying_252,
  title = {{Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09386-classifying-sequences-of-extreme-length-with-constant-memory-applied-to-malware-detection/},
}

@inproceedings{icml2024_caduceus_45294,
  title = {{Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33158},
}

@inproceedings{neurips2024_prosst_70451,
  title = {{ProSST: Protein Language Modeling with Quantized Structure and Disentangled Attention}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96656},
}

@inproceedings{neurips2025_titans_75452,
  title = {{Titans: Learning to Memorize at Test Time}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=8GjSf9Rh7Z},
}

@inproceedings{cvpr2024_skeleton_24832,
  title = {{Skeleton-in-Context: Unified Skeleton Sequence Modeling with In-Context Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30342},
}

@inproceedings{icml2025_learning_49006,
  title = {{Learning to (Learn at Test Time): RNNs with Expressive Hidden States}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43617},
}

@inproceedings{aaai2025_cognitive_8450,
  title = {{Cognitive Fluctuations Enhanced Attention Network for Knowledge Tracing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33562},
}

@inproceedings{neurips2024_hydra_73991,
  title = {{Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93526},
}

@inproceedings{cvpr2024_towards_25030,
  title = {{Towards Automated Movie Trailer Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29320},
}

@inproceedings{neurips2024_theoretical_70354,
  title = {{Theoretical Foundations of Deep Selective State-Space Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96743},
}

@inproceedings{iclr2025_bio_81623,
  title = {{Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30154},
}

@inproceedings{aaai2024_neural_6763,
  title = {{Neural Embeddings for kNN Search in Biological Sequence}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27753},
}

@inproceedings{iclr2025_samba_82683,
  title = {{Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29115},
}

@inproceedings{iclr2024_never_34377,
  title = {{Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18698},
}

@inproceedings{neurips2024_the_73169,
  title = {{The Expressive Capacity of State Space Models: A Formal Language Perspective}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94264},
}

@inproceedings{neurips2024_dataset_74076,
  title = {{Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93454},
}

@inproceedings{aaai2025_docmamba_8790,
  title = {{DocMamba: Efficient Document Pre-training with State Space Model}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34584},
}

@inproceedings{neurips2024_understanding_73448,
  title = {{Understanding the Differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94017},
}

@inproceedings{cvpr2024_masked_24115,
  title = {{Masked AutoDecoder is Effective Multi-Task Vision Generalist}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31068},
}

@inproceedings{neurips2025_edeline_79468,
  title = {{EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=ph1V6n7BSv},
}

@inproceedings{icml2024_state_43848,
  title = {{State-Free Inference of State-Space Models: The *Transfer Function* Approach}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34604},
}