% references_part05.bib — Part V (The Artificial Intelligence Transformation), WP44. Generated by
% literature_synthesis/agent_E/make_bib_part05.py on 2026-11-03: every entry resolved by one Crossref (DOI) or arXiv lookup;
% see references_verification_part05.csv. Keys of manuscript/references.bib are not redefined here.

@article{bick2026rapidadoption,
  title = {{The Rapid Adoption of Generative AI}},
  author = {Bick, Alexander and Blandin, Adam and Deming, David J.},
  year = {2026},
  journal = {Management Science},
  volume = {72},
  number = {10},
  pages = {8440--8456},
  doi = {10.1287/mnsc.2025.02523}
}

@article{kasneci2023chatgptgood,
  title = {{ChatGPT for good? On opportunities and challenges of large language models for education}},
  author = {Kasneci, Enkelejda and Sessler, Kathrin and Küchemann, Stefan and Bannert, Maria and Dementieva, Daryna and Fischer, Frank and Gasser, Urs and Groh, Georg and Günnemann, Stephan and Hüllermeier, Eyke and Krusche, Stephan and Kutyniok, Gitta and Michaeli, Tilman and Nerdel, Claudia and Pfeffer, Jürgen and Poquet, Oleksandra and Sailer, Michael and Schmidt, Albrecht and Seidel, Tina and Stadler, Matthias and Weller, Jochen and Kuhn, Jochen and Kasneci, Gjergji},
  year = {2023},
  journal = {Learning and Individual Differences},
  volume = {103},
  pages = {102274},
  doi = {10.1016/j.lindif.2023.102274}
}

@misc{wang2019superglue,
  title = {{SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems}},
  author = {Wang, Alex and Pruksachatkun, Yada and Nangia, Nikita and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R.},
  year = {2019},
  eprint = {1905.00537},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:1905.00537},
  note = {Preprint, not peer reviewed}
}

@misc{han2024peftsurvey,
  title = {{Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey}},
  author = {Han, Zeyu and Gao, Chao and Liu, Jinyang and Zhang, Jeff and Zhang, Sai Qian},
  year = {2024},
  eprint = {2403.14608},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:2403.14608},
  note = {Preprint, not peer reviewed}
}

@article{bodnar2025aurora,
  title = {{A foundation model for the Earth system}},
  author = {Bodnar, Cristian and Bruinsma, Wessel P. and Lucic, Ana and Stanley, Megan and Allen, Anna and Brandstetter, Johannes and Garvan, Patrick and Riechert, Maik and Weyn, Jonathan A. and Dong, Haiyu and Gupta, Jayesh K. and Thambiratnam, Kit and Archibald, Alexander T. and Wu, Chun-Chieh and Heider, Elizabeth and Welling, Max and Turner, Richard E. and Perdikaris, Paris},
  year = {2025},
  journal = {Nature},
  volume = {641},
  number = {8065},
  pages = {1180--1187},
  doi = {10.1038/s41586-025-09005-y}
}

@article{chen2024uni,
  title = {{Towards a general-purpose foundation model for computational pathology}},
  author = {Chen, Richard J. and Ding, Tong and Lu, Ming Y. and Williamson, Drew F. K. and Jaume, Guillaume and Song, Andrew H. and Chen, Bowen and Zhang, Andrew and Shao, Daniel and Shaban, Muhammad and Williams, Mane and Oldenburg, Lukas and Weishaupt, Luca L. and Wang, Judy J. and Vaidya, Anurag and Le, Long Phi and Gerber, Georg and Sahai, Sharifa and Williams, Walt and Mahmood, Faisal},
  year = {2024},
  journal = {Nature Medicine},
  volume = {30},
  number = {3},
  pages = {850--862},
  doi = {10.1038/s41591-024-02857-3}
}

@article{wang2024chief,
  title = {{A pathology foundation model for cancer diagnosis and prognosis prediction}},
  author = {Wang, Xiyue and Zhao, Junhan and Marostica, Eliana and Yuan, Wei and Jin, Jietian and Zhang, Jiayu and Li, Ruijiang and Tang, Hongping and Wang, Kanran and Li, Yu and Wang, Fang and Peng, Yulong and Zhu, Junyou and Zhang, Jing and Jackson, Christopher R. and Zhang, Jun and Dillon, Deborah and Lin, Nancy U. and Sholl, Lynette and Denize, Thomas and Meredith, David and Ligon, Keith L. and Signoretti, Sabina and Ogino, Shuji and Golden, Jeffrey A. and Nasrallah, MacLean P. and Han, Xiao and Yang, Sen and Yu, Kun-Hsing},
  year = {2024},
  journal = {Nature},
  volume = {634},
  number = {8035},
  pages = {970--978},
  doi = {10.1038/s41586-024-07894-z}
}

@article{zhang2024biomedgpt,
  title = {{A generalist vision--language foundation model for diverse biomedical tasks}},
  author = {Zhang, Kai and Zhou, Rong and Adhikarla, Eashan and Yan, Zhiling and Liu, Yixin and Yu, Jun and Liu, Zhengliang and Chen, Xun and Davison, Brian D. and Ren, Hui and Huang, Jing and Chen, Chen and Zhou, Yuyin and Fu, Sunyang and Liu, Wei and Liu, Tianming and Li, Xiang and Chen, Yong and He, Lifang and Zou, James and Li, Quanzheng and Liu, Hongfang and Sun, Lichao},
  year = {2024},
  journal = {Nature Medicine},
  volume = {30},
  number = {11},
  pages = {3129--3141},
  doi = {10.1038/s41591-024-03185-2}
}

@article{binz2025centaur,
  title = {{A foundation model to predict and capture human cognition}},
  author = {Binz, Marcel and Akata, Elif and Bethge, Matthias and Brändle, Franziska and Callaway, Fred and Coda-Forno, Julian and Dayan, Peter and Demircan, Can and Eckstein, Maria K. and Éltető, Noémi and Griffiths, Thomas L. and Haridi, Susanne and Jagadish, Akshay K. and Ji-An, Li and Kipnis, Alexander and Kumar, Sreejan and Ludwig, Tobias and Mathony, Marvin and Mattar, Marcelo and Modirshanechi, Alireza and Nath, Surabhi S. and Peterson, Joshua C. and Rmus, Milena and Russek, Evan M. and Saanum, Tankred and Schubert, Johannes A. and Schulze Buschoff, Luca M. and Singhi, Nishad and Sui, Xin and Thalmann, Mirko and Theis, Fabian J. and Truong, Vuong and Udandarao, Vishaal and Voudouris, Konstantinos and Wilson, Robert and Witte, Kristin and Wu, Shuchen and Wulff, Dirk U. and Xiong, Huadong and Schulz, Eric},
  year = {2025},
  journal = {Nature},
  volume = {644},
  number = {8078},
  pages = {1002--1009},
  doi = {10.1038/s41586-025-09215-4}
}

@misc{dai2023instructblip,
  title = {{InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning}},
  author = {Dai, Wenliang and Li, Junnan and Li, Dongxu and Tiong, Anthony Meng Huat and Zhao, Junqi and Wang, Weisheng and Li, Boyang and Fung, Pascale and Hoi, Steven},
  year = {2023},
  eprint = {2305.06500},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:2305.06500},
  note = {Preprint, not peer reviewed}
}

@misc{schuhmann2022laion5b,
  title = {{LAION-5B: An open large-scale dataset for training next generation image-text models}},
  author = {Schuhmann, Christoph and Beaumont, Romain and Vencu, Richard and Gordon, Cade and Wightman, Ross and Cherti, Mehdi and Coombes, Theo and Katta, Aarush and Mullis, Clayton and Wortsman, Mitchell and Schramowski, Patrick and Kundurthy, Srivatsa and Crowson, Katherine and Schmidt, Ludwig and Kaczmarczyk, Robert and Jitsev, Jenia},
  year = {2022},
  eprint = {2210.08402},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:2210.08402},
  note = {Preprint, not peer reviewed}
}

@misc{su2019vlbert,
  title = {{VL-BERT: Pre-training of Generic Visual-Linguistic Representations}},
  author = {Su, Weijie and Zhu, Xizhou and Cao, Yue and Li, Bin and Lu, Lewei and Wei, Furu and Dai, Jifeng},
  year = {2019},
  eprint = {1908.08530},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:1908.08530},
  note = {Preprint, not peer reviewed}
}

@article{mou2024t2iadapter,
  title = {{T2I-Adapter: Learning Adapters to Dig Out More Controllable Ability for Text-to-Image Diffusion Models}},
  author = {Mou, Chong and Wang, Xintao and Xie, Liangbin and Wu, Yanze and Zhang, Jian and Qi, Zhongang and Shan, Ying},
  year = {2024},
  journal = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {38},
  number = {5},
  pages = {4296--4304},
  doi = {10.1609/aaai.v38i5.28226}
}

@misc{gal2022textualinversion,
  title = {{An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion}},
  author = {Gal, Rinon and Alaluf, Yuval and Atzmon, Yuval and Patashnik, Or and Bermano, Amit H. and Chechik, Gal and Cohen-Or, Daniel},
  year = {2022},
  eprint = {2208.01618},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:2208.01618},
  note = {Preprint, not peer reviewed}
}

@article{buckley2026textexploit,
  title = {{Multimodal foundation models exploit text to make medical image predictions}},
  author = {Buckley, Thomas A. and Diao, James A. and Srivastava, Cam N. and Brodeur, Peter G. and Rajpurkar, Pranav and Rodman, Adam and Manrai, Arjun K.},
  year = {2026},
  journal = {Nature Communications},
  volume = {17},
  number = {1},
  doi = {10.1038/s41467-026-74207-5}
}

@article{zhang2026lowqualityfusion,
  title = {{Multimodal fusion on low-quality data: A comprehensive survey}},
  author = {Zhang, Qingyang and Wei, Yake and Han, Zongbo and Fu, Huazhu and Peng, Xi and Hu, Qinghua and Deng, Cheng and Xu, Cai and Wen, Jie and Hu, Di and Zhang, Changqing},
  year = {2026},
  journal = {Information Fusion},
  volume = {135},
  pages = {104437},
  doi = {10.1016/j.inffus.2026.104437}
}

@misc{ho2022cfg,
  title = {{Classifier-Free Diffusion Guidance}},
  author = {Ho, Jonathan and Salimans, Tim},
  year = {2022},
  eprint = {2207.12598},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:2207.12598},
  note = {Preprint, not peer reviewed}
}

@article{zeni2025mattergen,
  title = {{A generative model for inorganic materials design}},
  author = {Zeni, Claudio and Pinsler, Robert and Zügner, Daniel and Fowler, Andrew and Horton, Matthew and Fu, Xiang and Wang, Zilong and Shysheya, Aliaksandra and Crabbé, Jonathan and Ueda, Shoko and Sordillo, Roberto and Sun, Lixin and Smith, Jake and Nguyen, Bichlien and Schulz, Hannes and Lewis, Sarah and Huang, Chin-Wei and Lu, Ziheng and Zhou, Yichi and Yang, Han and Hao, Hongxia and Li, Jielan and Yang, Chunlei and Li, Wenjie and Tomioka, Ryota and Xie, Tian},
  year = {2025},
  journal = {Nature},
  volume = {639},
  number = {8055},
  pages = {624--632},
  doi = {10.1038/s41586-025-08628-5}
}

@misc{bastani2024harmlearning,
  title = {{Generative AI Can Harm Learning}},
  author = {Bastani, Hamsa and Bastani, Osbert and Sungu, Alp and Ge, Haosen and Kabakcı, Özge and Mariman, Rei},
  year = {2024},
  howpublished = {Preprint (Elsevier BV)},
  note = {Preprint, not peer reviewed},
  doi = {10.2139/ssrn.4895486}
}

@article{acharya2025agenticsurvey,
  title = {{Agentic AI: Autonomous Intelligence for Complex Goals---A Comprehensive Survey}},
  author = {Acharya, Deepak Bhaskar and Kuppan, Karthigeyan and Divya, B.},
  year = {2025},
  journal = {IEEE Access},
  volume = {13},
  pages = {18912--18936},
  doi = {10.1109/access.2025.3532853}
}

@article{ghareeb2026robin,
  title = {{A multi-agent system for automating scientific discovery}},
  author = {Ghareeb, Ali E. and Chang, Benjamin and Mitchener, Ludovico and Yiu, Angela and Szostkiewicz, Caralyn J. and Shved, Dmytro and Gyimesi, Gavin J. and Laurent, Jon M. and Wright, Samantha M. and Razzak, Muhammed T. and White, Andrew D. and Finnemann, Silvia C. and Hinks, Michaela M. and Rodriques, Samuel G.},
  year = {2026},
  journal = {Nature},
  volume = {655},
  number = {8122},
  pages = {497--505},
  doi = {10.1038/s41586-026-10652-y}
}

@article{swanson2025virtuallab,
  title = {{The Virtual Lab of AI agents designs new SARS-CoV-2 nanobodies}},
  author = {Swanson, Kyle and Wu, Wesley and Bulaong, Nash L. and Pak, John E. and Zou, James},
  year = {2025},
  journal = {Nature},
  volume = {646},
  number = {8085},
  pages = {716--723},
  doi = {10.1038/s41586-025-09442-9}
}

@article{piao2026agentsociety,
  title = {{AgentSociety: Large-scale simulation of LLM-driven generative agents advances understanding of human behaviors and society}},
  author = {Piao, Jinghua and Yan, Yuwei and Zhang, Jun and Li, Nian and Yan, Junbo and Lan, Xiaochong and Lu, Zhihong and Zheng, Zhiheng and Wang, Jing Yi and Zhou, Di and Gao, Chen and Xu, Fengli and Zhang, Fang and Rong, Ke and Su, Jun and Li, Yong},
  year = {2026},
  journal = {iFuture},
  doi = {10.26599/if.2026.9710004}
}

@article{sapkota2026agentsvsagentic,
  title = {{AI Agents vs. Agentic AI: A Conceptual taxonomy, applications and challenges}},
  author = {Sapkota, Ranjan and Roumeliotis, Konstantinos I. and Karkee, Manoj},
  year = {2026},
  journal = {Information Fusion},
  volume = {126},
  pages = {103599},
  doi = {10.1016/j.inffus.2025.103599}
}

@article{zhang2025agentmemory,
  title = {{A Survey on the Memory Mechanism of Large Language Model-based Agents}},
  author = {Zhang, Zeyu and Dai, Quanyu and Bo, Xiaohe and Ma, Chen and Li, Rui and Chen, Xu and Zhu, Jieming and Dong, Zhenhua and Wen, Ji-Rong},
  year = {2025},
  journal = {ACM Transactions on Information Systems},
  volume = {43},
  number = {6},
  pages = {1--47},
  doi = {10.1145/3748302}
}

@article{liu2026clinicalagents,
  title = {{Benchmarking large language model-based agent systems for clinical decision tasks}},
  author = {Liu, Yunsong and Carrero, Zunamys I. and Jiang, Xiaofeng and Ferber, Dyke and Wölflein, Georg and Zhang, Li and Jayabalan, Sanddhya and Lenz, Tim and Hui, Zhouguang and Kather, Jakob Nikolas},
  year = {2026},
  journal = {npj Digital Medicine},
  volume = {9},
  number = {1},
  doi = {10.1038/s41746-026-02443-6}
}

@misc{haarnoja2018sac,
  title = {{Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor}},
  author = {Haarnoja, Tuomas and Zhou, Aurick and Abbeel, Pieter and Levine, Sergey},
  year = {2018},
  eprint = {1801.01290},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:1801.01290},
  note = {Preprint, not peer reviewed}
}

@misc{fujimoto2018td3,
  title = {{Addressing Function Approximation Error in Actor-Critic Methods}},
  author = {Fujimoto, Scott and Hoof, Herke van and Meger, David},
  year = {2018},
  eprint = {1802.09477},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:1802.09477},
  note = {Preprint, not peer reviewed}
}

@article{vinyals2019alphastar,
  title = {{Grandmaster level in StarCraft II using multi-agent reinforcement learning}},
  author = {Vinyals, Oriol and Babuschkin, Igor and Czarnecki, Wojciech M. and Mathieu, Michaël and Dudzik, Andrew and Chung, Junyoung and Choi, David H. and Powell, Richard and Ewalds, Timo and Georgiev, Petko and Oh, Junhyuk and Horgan, Dan and Kroiss, Manuel and Danihelka, Ivo and Huang, Aja and Sifre, Laurent and Cai, Trevor and Agapiou, John P. and Jaderberg, Max and Vezhnevets, Alexander S. and Leblond, Rémi and Pohlen, Tobias and Dalibard, Valentin and Budden, David and Sulsky, Yury and Molloy, James and Paine, Tom L. and Gulcehre, Caglar and Wang, Ziyu and Pfaff, Tobias and Wu, Yuhuai and Ring, Roman and Yogatama, Dani and Wünsch, Dario and McKinney, Katrina and Smith, Oliver and Schaul, Tom and Lillicrap, Timothy and Kavukcuoglu, Koray and Hassabis, Demis and Apps, Chris and Silver, David},
  year = {2019},
  journal = {Nature},
  volume = {575},
  number = {7782},
  pages = {350--354},
  doi = {10.1038/s41586-019-1724-z}
}

@article{hessel2018rainbow,
  title = {{Rainbow: Combining Improvements in Deep Reinforcement Learning}},
  author = {Hessel, Matteo and Modayil, Joseph and Van Hasselt, Hado and Schaul, Tom and Ostrovski, Georg and Dabney, Will and Horgan, Dan and Piot, Bilal and Azar, Mohammad and Silver, David},
  year = {2018},
  journal = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {32},
  number = {1},
  doi = {10.1609/aaai.v32i1.11796}
}

@misc{yu2021mappo,
  title = {{The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games}},
  author = {Yu, Chao and Velu, Akash and Vinitsky, Eugene and Gao, Jiaxuan and Wang, Yu and Bayen, Alexandre and Wu, Yi},
  year = {2021},
  eprint = {2103.01955},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:2103.01955},
  note = {Preprint, not peer reviewed}
}

@article{hafner2025dreamerv3,
  title = {{Mastering diverse control tasks through world models}},
  author = {Hafner, Danijar and Pasukonis, Jurgis and Ba, Jimmy and Lillicrap, Timothy},
  year = {2025},
  journal = {Nature},
  volume = {640},
  number = {8059},
  pages = {647--653},
  doi = {10.1038/s41586-025-08744-2}
}

@misc{burda2018curiosity,
  title = {{Large-Scale Study of Curiosity-Driven Learning}},
  author = {Burda, Yuri and Edwards, Harri and Pathak, Deepak and Storkey, Amos and Darrell, Trevor and Efros, Alexei A.},
  year = {2018},
  eprint = {1808.04355},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:1808.04355},
  note = {Preprint, not peer reviewed}
}

@incollection{zhang2021marloverview,
  title = {{Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms}},
  author = {Zhang, Kaiqing and Yang, Zhuoran and Başar, Tamer},
  year = {2021},
  booktitle = {Studies in Systems, Decision and Control},
  publisher = {Springer International Publishing},
  pages = {321--384},
  doi = {10.1007/978-3-030-60990-0_12}
}

@article{rudin2019stopexplaining,
  title = {{Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead}},
  author = {Rudin, Cynthia},
  year = {2019},
  journal = {Nature Machine Intelligence},
  volume = {1},
  number = {5},
  pages = {206--215},
  doi = {10.1038/s42256-019-0048-x}
}

@article{lipton2018mythos,
  title = {{The mythos of model interpretability}},
  author = {Lipton, Zachary C.},
  year = {2018},
  journal = {Communications of the ACM},
  volume = {61},
  number = {10},
  pages = {36--43},
  doi = {10.1145/3233231}
}

@article{lundberg2020treeexplainer,
  title = {{From local explanations to global understanding with explainable AI for trees}},
  author = {Lundberg, Scott M. and Erion, Gabriel and Chen, Hugh and DeGrave, Alex and Prutkin, Jordan M. and Nair, Bala and Katz, Ronit and Himmelfarb, Jonathan and Bansal, Nisha and Lee, Su-In},
  year = {2020},
  journal = {Nature Machine Intelligence},
  volume = {2},
  number = {1},
  pages = {56--67},
  doi = {10.1038/s42256-019-0138-9}
}

@article{chicco2020mcc,
  title = {{The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation}},
  author = {Chicco, Davide and Jurman, Giuseppe},
  year = {2020},
  journal = {BMC Genomics},
  volume = {21},
  number = {1},
  doi = {10.1186/s12864-019-6413-7}
}

@article{zhuang2021transfersurvey,
  title = {{A Comprehensive Survey on Transfer Learning}},
  author = {Zhuang, Fuzhen and Qi, Zhiyuan and Duan, Keyu and Xi, Dongbo and Zhu, Yongchun and Zhu, Hengshu and Xiong, Hui and He, Qing},
  year = {2021},
  journal = {Proceedings of the IEEE},
  volume = {109},
  number = {1},
  pages = {43--76},
  doi = {10.1109/jproc.2020.3004555}
}

@article{bottou2018optimization,
  title = {{Optimization Methods for Large-Scale Machine Learning}},
  author = {Bottou, Léon and Curtis, Frank E. and Nocedal, Jorge},
  year = {2018},
  journal = {SIAM Review},
  volume = {60},
  number = {2},
  pages = {223--311},
  doi = {10.1137/16m1080173}
}

@article{zeng2023transformerstsf,
  title = {{Are Transformers Effective for Time Series Forecasting?}},
  author = {Zeng, Ailing and Chen, Muxi and Zhang, Lei and Xu, Qiang},
  year = {2023},
  journal = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {37},
  number = {9},
  pages = {11121--11128},
  doi = {10.1609/aaai.v37i9.26317}
}

@article{zhou2021informer,
  title = {{Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting}},
  author = {Zhou, Haoyi and Zhang, Shanghang and Peng, Jieqi and Zhang, Shuai and Li, Jianxin and Xiong, Hui and Zhang, Wancai},
  year = {2021},
  journal = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {35},
  number = {12},
  pages = {11106--11115},
  doi = {10.1609/aaai.v35i12.17325}
}

@inproceedings{wen2023tstransformers,
  title = {{Transformers in Time Series: A Survey}},
  author = {Wen, Qingsong and Zhou, Tian and Zhang, Chaoli and Chen, Weiqi and Ma, Ziqing and Yan, Junchi and Sun, Liang},
  year = {2023},
  booktitle = {Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence},
  pages = {6778--6786},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  doi = {10.24963/ijcai.2023/759}
}

@article{hollmann2025tabpfn,
  title = {{Accurate predictions on small data with a tabular foundation model}},
  author = {Hollmann, Noah and Müller, Samuel and Purucker, Lennart and Krishnakumar, Arjun and Körfer, Max and Hoo, Shi Bin and Schirrmeister, Robin Tibor and Hutter, Frank},
  year = {2025},
  journal = {Nature},
  volume = {637},
  number = {8045},
  pages = {319--326},
  doi = {10.1038/s41586-024-08328-6}
}

@misc{liu2024kan,
  title = {{KAN: Kolmogorov-Arnold Networks}},
  author = {Liu, Ziming and Wang, Yixuan and Vaidya, Sachin and Ruehle, Fabian and Halverson, James and Soljačić, Marin and Hou, Thomas Y. and Tegmark, Max},
  year = {2024},
  eprint = {2404.19756},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:2404.19756},
  note = {Preprint, not peer reviewed}
}

@article{wu2021gnnsurvey,
  title = {{A Comprehensive Survey on Graph Neural Networks}},
  author = {Wu, Zonghan and Pan, Shirui and Chen, Fengwen and Long, Guodong and Zhang, Chengqi and Yu, Philip S.},
  year = {2021},
  journal = {IEEE Transactions on Neural Networks and Learning Systems},
  volume = {32},
  number = {1},
  pages = {4--24},
  doi = {10.1109/tnnls.2020.2978386}
}

@article{zhou2020gnnreview,
  title = {{Graph neural networks: A review of methods and applications}},
  author = {Zhou, Jie and Cui, Ganqu and Hu, Shengding and Zhang, Zhengyan and Yang, Cheng and Liu, Zhiyuan and Wang, Lifeng and Li, Changcheng and Sun, Maosong},
  year = {2020},
  journal = {AI Open},
  volume = {1},
  pages = {57--81},
  doi = {10.1016/j.aiopen.2021.01.001}
}

@misc{zhang2017mixup,
  title = {{mixup: Beyond Empirical Risk Minimization}},
  author = {Zhang, Hongyi and Cisse, Moustapha and Dauphin, Yann N. and Lopez-Paz, David},
  year = {2017},
  eprint = {1710.09412},
  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:1710.09412},
  note = {Preprint, not peer reviewed}
}

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  archiveprefix = {arXiv},
  howpublished = {arXiv preprint arXiv:2303.16199},
  note = {Preprint, not peer reviewed}
}