@inproceedings{
Li2020Rethinking,
title={Rethinking the Hyperparameters for Fine-tuning},
author={Hao Li and Pratik Chaudhari and Hao Yang and Michael Lam and Avinash Ravichandran and Rahul Bhotika and Stefano Soatto},
booktitle={International Conference on Learning Representations},
year={2020},
url={https://openreview.net/forum?id=B1g8VkHFPH}
}

@inproceedings{
lee2023surgical,
title={Surgical Fine-Tuning Improves Adaptation to Distribution Shifts},
author={Yoonho Lee and Annie S Chen and Fahim Tajwar and Ananya Kumar and Huaxiu Yao and Percy Liang and Chelsea Finn},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=APuPRxjHvZ}
}


@article{osti_10426834,
place = {Country unknown/Code not available}, title = {A Theoretical Study on Solving Continual Learning}, url = {https://par.nsf.gov/biblio/10426834}, abstractNote = {}, journal = {Proceedings of Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS-2022)}, author = {Kim, Gyuhak and Xiao, Changnan and Konishi, Tatsuya and Ke, Zixuan and Liu, Bing}, }
@inproceedings{
fang2022is,
title={Is Out-of-Distribution Detection Learnable?},
author={Zhen Fang and Yixuan Li and Jie Lu and Jiahua Dong and Bo Han and Feng Liu},
booktitle={Advances in Neural Information Processing Systems},
editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
year={2022},
}
@inproceedings{
kvinge2022in,
title={In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?},
author={Henry Kvinge and Tegan Emerson and Grayson Jorgenson and Scott Vasquez and Timothy Doster and Jesse Lew},
booktitle={Advances in Neural Information Processing Systems},
editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
year={2022},
url={https://openreview.net/forum?id=SCD0hn3kMHw}
}
@article{DBLP:journals/corr/abs-2102-12232,
  author       = {Kenshin Abe and
                  Takanori Maehara and
                  Issei Sato},
  title        = {Abelian Neural Networks},
  journal      = {CoRR},
  volume       = {abs/2102.12232},
  year         = {2021},
  url          = {https://arxiv.org/abs/2102.12232},
  eprinttype    = {arXiv},
  eprint       = {2102.12232},
  timestamp    = {Tue, 02 Mar 2021 12:11:01 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2102-12232.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{
hiller2022rethinking,
title={Rethinking Generalization in Few-Shot Classification},
author={Markus Hiller and Rongkai Ma and Mehrtash Harandi and Tom Drummond},
booktitle={Advances in Neural Information Processing Systems},
editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
year={2022},
url={https://openreview.net/forum?id=p_g2nHlMus}
}

@inproceedings{
korotin2022kantorovich,
title={Kantorovich Strikes Back! Wasserstein {GAN}s are not Optimal Transport?},
author={Alexander Korotin and Alexander Kolesov and Evgeny Burnaev},
booktitle={Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
year={2022},
url={https://openreview.net/forum?id=VtEEpi-dGlt}
}
@inproceedings{
alvarez-melis2022are,
title={Are {GAN}s overkill for {NLP}?},
author={David Alvarez-Melis and Vikas K Garg and Adam Tauman Kalai},
booktitle={Advances in Neural Information Processing Systems},
editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
year={2022},
url={https://openreview.net/forum?id=F02H1zNl213}
}

@inproceedings{
zhang2023rethinking,
title={Rethinking the Expressive Power of {GNN}s via Graph Biconnectivity},
author={Bohang Zhang and Shengjie Luo and Liwei Wang and Di He},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=r9hNv76KoT3}
}

@inproceedings{
yuksekgonul2023when,
title={When and Why Vision-Language Models Behave like Bags-Of-Words, and What to Do About It?},
author={Mert Yuksekgonul and Federico Bianchi and Pratyusha Kalluri and Dan Jurafsky and James Zou},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=KRLUvxh8uaX}
}

@inproceedings{
allen-zhu2023towards,
title={Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning},
author={Zeyuan Allen-Zhu and Yuanzhi Li},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=Uuf2q9TfXGA}
}

@article{sportisse2023labels,
  title={Are labels informative in semi-supervised learning?--Estimating and leveraging the missing-data mechanism},
  author={Sportisse, Aude and Schmutz, Hugo and Humbert, Olivier and Bouveyron, Charles and Mattei, Pierre-Alexandre},
  journal={arXiv preprint arXiv:2302.07540},
  year={2023}
}@article{sportisse2023labels,
  title={Are labels informative in semi-supervised learning?--Estimating and leveraging the missing-data mechanism},
  author={Sportisse, Aude and Schmutz, Hugo and Humbert, Olivier and Bouveyron, Charles and Mattei, Pierre-Alexandre},
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  year={2023}
}

@inproceedings{DBLP:conf/icml/Zhao0LJZ23,
  author       = {Haiyan Zhao and
                  Tianyi Zhou and
                  Guodong Long and
                  Jing Jiang and
                  Chengqi Zhang},
  editor       = {Andreas Krause and
                  Emma Brunskill and
                  Kyunghyun Cho and
                  Barbara Engelhardt and
                  Sivan Sabato and
                  Jonathan Scarlett},
  title        = {Does Continual Learning Equally Forget All Parameters?},
  booktitle    = {International Conference on Machine Learning, {ICML} 2023, 23-29 July
                  2023, Honolulu, Hawaii, {USA}},
  series       = {Proceedings of Machine Learning Research},
  volume       = {202},
  pages        = {42280--42303},
  publisher    = {{PMLR}},
  year         = {2023},
  url          = {https://proceedings.mlr.press/v202/zhao23n.html},
}

@inproceedings{
yong2022zin,
title={{ZIN}: When and How to Learn Invariance Without Environment Partition?},
author={LIN Yong and Shengyu Zhu and Lu Tan and Peng Cui},
booktitle={Advances in Neural Information Processing Systems},
editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
year={2022},
url={https://openreview.net/forum?id=pUPFRSxfACD}
}

@inproceedings{
allen-zhu2023towards,
title={Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning},
author={Zeyuan Allen-Zhu and Yuanzhi Li},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=Uuf2q9TfXGA}
}
@article{yang2023bayesian,
  title={Bayesian low-rank adaptation for large language models},
  author={Yang, Adam X and Robeyns, Maxime and Wang, Xi and Aitchison, Laurence},
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}

@inproceedings{chen-etal-2022-revisiting,
    title = "Revisiting Parameter-Efficient Tuning: Are We Really There Yet?",
    author = "Chen, Guanzheng  and
      Liu, Fangyu  and
      Meng, Zaiqiao  and
      Liang, Shangsong",
    editor = "Goldberg, Yoav  and
      Kozareva, Zornitsa  and
      Zhang, Yue",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates",
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    url = "https://aclanthology.org/2022.emnlp-main.168",
    doi = "10.18653/v1/2022.emnlp-main.168",
    pages = "2612--2626",
}

@inproceedings{zhang2019your,
  title={Be your own teacher: Improve the performance of convolutional neural networks via self distillation},
  author={Zhang, Linfeng and Song, Jiebo and Gao, Anni and Chen, Jingwei and Bao, Chenglong and Ma, Kaisheng},
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}


@InProceedings{pmlr-v139-bahri21a,
  title = 	 {Locally Adaptive Label Smoothing Improves Predictive Churn},
  author =       {Bahri, Dara and Jiang, Heinrich},
  booktitle = 	 {Proceedings of the 38th International Conference on Machine Learning},
  pages = 	 {532--542},
  year = 	 {2021},
  editor = 	 {Meila, Marina and Zhang, Tong},
  volume = 	 {139},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {18--24 Jul},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v139/bahri21a/bahri21a.pdf},
  url = 	 {https://proceedings.mlr.press/v139/bahri21a.html},
}

@inproceedings{
mosbach2021on,
title={On the Stability of Fine-tuning BERT Misconceptions, Explanations, and Strong Baselines},
author={Marius Mosbach and Maksym Andriushchenko and Dietrich Klakow},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=nzpLWnVAyah}
}

@inproceedings{zhou-srikumar-2022-closer,
    title = "A Closer Look at How Fine-tuning Changes {BERT}",
    author = "Zhou, Yichu  and
      Srikumar, Vivek",
    editor = "Muresan, Smaranda  and
      Nakov, Preslav  and
      Villavicencio, Aline",
    booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = may,
    year = "2022",
    address = "Dublin, Ireland",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.acl-long.75",
    doi = "10.18653/v1/2022.acl-long.75",
    pages = "1046--1061",
}

@inproceedings{
hu2022lora,
title={Lo{RA}: Low-Rank Adaptation of Large Language Models},
author={Edward J Hu and yelong shen and Phillip Wallis and Zeyuan Allen-Zhu and Yuanzhi Li and Shean Wang and Lu Wang and Weizhu Chen},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=nZeVKeeFYf9}
}

@inproceedings{datta-etal-2023-measuring,
    title = "Measuring and Mitigating Local Instability in Deep Neural Networks",
    author = "Datta, Arghya  and
      Nandi, Subhrangshu  and
      Xu, Jingcheng  and
      Ver Steeg, Greg  and
      Xie, He  and
      Kumar, Anoop  and
      Galstyan, Aram",
    editor = "Rogers, Anna  and
      Boyd-Graber, Jordan  and
      Okazaki, Naoaki",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.findings-acl.176",
    doi = "10.18653/v1/2023.findings-acl.176",
    pages = "2810--2823",
}

@inproceedings{
jiang2022churn,
title={Churn Reduction via Distillation},
author={Heinrich Jiang and Harikrishna Narasimhan and Dara Bahri and Andrew Cotter and Afshin Rostamizadeh},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=HbtFCX2PLq0}
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he2022towards,
title={Towards a Unified View of Parameter-Efficient Transfer Learning},
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    title = "Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning",
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      Xia, Fei  and
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      Navigli, Roberto",
    booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
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    address = "Online",
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    url = "https://aclanthology.org/2021.acl-long.568",
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}
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@article{wang2018glue,
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  author={Wang, Alex and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R},
  journal={arXiv preprint arXiv:1804.07461},
  year={2018}
}

@inproceedings{tian-etal-2023-just,
    title = "Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback",
    author = "Tian, Katherine  and
      Mitchell, Eric  and
      Zhou, Allan  and
      Sharma, Archit  and
      Rafailov, Rafael  and
      Yao, Huaxiu  and
      Finn, Chelsea  and
      Manning, Christopher",
    editor = "Bouamor, Houda  and
      Pino, Juan  and
      Bali, Kalika",
    booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.emnlp-main.330",
    pages = "5433--5442",

}

@article{devlin2018bert,
  title={Bert: Pre-training of deep bidirectional transformers for language understanding},
  author={Devlin, Jacob and Chang, Ming-Wei and Lee, Kenton and Toutanova, Kristina},
  journal={arXiv preprint arXiv:1810.04805},
  year={2018}
}

@article{kadavath2022language,
  title={Language models (mostly) know what they know},
  author={Kadavath, Saurav and Conerly, Tom and Askell, Amanda and Henighan, Tom and Drain, Dawn and Perez, Ethan and Schiefer, Nicholas and Hatfield-Dodds, Zac and DasSarma, Nova and Tran-Johnson, Eli and others},
  journal={arXiv preprint arXiv:2207.05221},
  year={2022}
}

@article{christiano2017deep,
  title={Deep reinforcement learning from human preferences},
  author={Christiano, Paul F and Leike, Jan and Brown, Tom and Martic, Miljan and Legg, Shane and Amodei, Dario},
  journal={Advances in neural information processing systems},
  volume={30},
  year={2017}
}

@article{hinton2015distilling,
  title={Distilling the knowledge in a neural network},
  author={Hinton, Geoffrey and Vinyals, Oriol and Dean, Jeff},
  journal={arXiv preprint arXiv:1503.02531},
  year={2015}
}

@inproceedings{he2016deep,
  title={Deep residual learning for image recognition},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={770--778},
  year={2016}
}

@article{jacot2018neural,
  title={Neural tangent kernel: Convergence and generalization in neural networks},
  author={Jacot, Arthur and Gabriel, Franck and Hongler, Cl{\'e}ment},
  journal={Advances in neural information processing systems},
  volume={31},
  year={2018}
}

@article{yuan2023learning,
  title={Learning From Biased Soft Labels},
  author={Yuan, Hua and Xu, Ning and Shi, Yu and Geng, Xin and Rui, Yong},
  journal={arXiv preprint arXiv:2302.08155},
  year={Advances in neural information processing systems}
}

@inproceedings{
huang2017snapshot,
title={Snapshot Ensembles: Train 1, Get M for Free},
author={Gao Huang and Yixuan Li and Geoff Pleiss and Zhuang Liu and John E. Hopcroft and Kilian Q. Weinberger},
booktitle={International Conference on Learning Representations},
year={2017},
url={https://openreview.net/forum?id=BJYwwY9ll}
}

@inproceedings{yang2019snapshot,
  title={Snapshot distillation: Teacher-student optimization in one generation},
  author={Yang, Chenglin and Xie, Lingxi and Su, Chi and Yuille, Alan L},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={2859--2868},
  year={2019}
}

@article{izmailov2018averaging,
  title={Averaging weights leads to wider optima and better generalization},
  author={Izmailov, Pavel and Podoprikhin, Dmitrii and Garipov, Timur and Vetrov, Dmitry and Wilson, Andrew Gordon},
  journal={arXiv preprint arXiv:1803.05407},
  year={2018}
}

@inproceedings{kobyzev-etal-2023-need,
    title = "Do we need Label Regularization to Fine-tune Pre-trained Language Models?",
    author = "Kobyzev, Ivan  and
      Jafari, Aref  and
      Rezagholizadeh, Mehdi  and
      Li, Tianda  and
      Do-Omri, Alan  and
      Lu, Peng  and
      Poupart, Pascal  and
      Ghodsi, Ali",
    editor = "Vlachos, Andreas  and
      Augenstein, Isabelle",
    booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics",
    month = may,
    year = "2023",
    address = "Dubrovnik, Croatia",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.eacl-main.13",
    doi = "10.18653/v1/2023.eacl-main.13",
    pages = "166--177",
}

@inproceedings{wei2022mitigating,
  title={Mitigating neural network overconfidence with logit normalization},
  author={Wei, Hongxin and Xie, Renchunzi and Cheng, Hao and Feng, Lei and An, Bo and Li, Yixuan},
  booktitle={International Conference on Machine Learning},
  pages={23631--23644},
  year={2022},
  organization={PMLR}
}

@inproceedings{lu-etal-2022-improving,
    title = "Improving Generalization of Pre-trained Language Models via Stochastic Weight Averaging",
    author = "Lu, Peng  and
      Kobyzev, Ivan  and
      Rezagholizadeh, Mehdi  and
      Rashid, Ahmad  and
      Ghodsi, Ali  and
      Langlais, Phillippe",
    editor = "Goldberg, Yoav  and
      Kozareva, Zornitsa  and
      Zhang, Yue",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2022",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.findings-emnlp.363",
    doi = "10.18653/v1/2022.findings-emnlp.363",
    pages = "4948--4954",
}

@article{team2023gemini,
  title={Gemini: A family of highly capable multimodal models},
  author={Team, Gemini and Anil, Rohan and Borgeaud, Sebastian and Wu, Yonghui and Alayrac, Jean-Baptiste and Yu, Jiahui and Soricut, Radu and Schalkwyk, Johan and Dai, Andrew M and Hauth, Anja and others},
  journal={arXiv preprint arXiv:2312.11805},
  year={2023}
}

@inproceedings{
seligmann2023beyond,
title={Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift},
author={Florian Seligmann and Philipp Becker and Michael Volpp and Gerhard Neumann},
booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
year={2023},
url={https://openreview.net/forum?id=jX49iKr6vb}
}

@article{bubeck2023sparks,
  title={Sparks of artificial general intelligence: Early experiments with gpt-4},
  author={Bubeck, S{\'e}bastien and Chandrasekaran, Varun and Eldan, Ronen and Gehrke, Johannes and Horvitz, Eric and Kamar, Ece and Lee, Peter and Lee, Yin Tat and Li, Yuanzhi and Lundberg, Scott and others},
  journal={arXiv preprint arXiv:2303.12712},
  year={2023}
}
@misc{openai2023gpt4,
      title={GPT-4 Technical Report},
      author={OpenAI and : and Josh Achiam and Steven Adler and Sandhini Agarwal and Lama Ahmad and Ilge Akkaya and Florencia Leoni Aleman and Diogo Almeida and Janko Altenschmidt and Sam Altman and Shyamal Anadkat and Red Avila and Igor Babuschkin and Suchir Balaji and Valerie Balcom and Paul Baltescu and Haiming Bao and Mo Bavarian and Jeff Belgum and Irwan Bello and Jake Berdine and Gabriel Bernadett-Shapiro and Christopher Berner and Lenny Bogdonoff and Oleg Boiko and Madelaine Boyd and Anna-Luisa Brakman and Greg Brockman and Tim Brooks and Miles Brundage and Kevin Button and Trevor Cai and Rosie Campbell and Andrew Cann and Brittany Carey and Chelsea Carlson and Rory Carmichael and Brooke Chan and Che Chang and Fotis Chantzis and Derek Chen and Sully Chen and Ruby Chen and Jason Chen and Mark Chen and Ben Chess and Chester Cho and Casey Chu and Hyung Won Chung and Dave Cummings and Jeremiah Currier and Yunxing Dai and Cory Decareaux and Thomas Degry and Noah Deutsch and Damien Deville and Arka Dhar and David Dohan and Steve Dowling and Sheila Dunning and Adrien Ecoffet and Atty Eleti and Tyna Eloundou and David Farhi and Liam Fedus and Niko Felix and Simón Posada Fishman and Juston Forte and Isabella Fulford and Leo Gao and Elie Georges and Christian Gibson and Vik Goel and Tarun Gogineni and Gabriel Goh and Rapha Gontijo-Lopes and Jonathan Gordon and Morgan Grafstein and Scott Gray and Ryan Greene and Joshua Gross and Shixiang Shane Gu and Yufei Guo and Chris Hallacy and Jesse Han and Jeff Harris and Yuchen He and Mike Heaton and Johannes Heidecke and Chris Hesse and Alan Hickey and Wade Hickey and Peter Hoeschele and Brandon Houghton and Kenny Hsu and Shengli Hu and Xin Hu and Joost Huizinga and Shantanu Jain and Shawn Jain and Joanne Jang and Angela Jiang and Roger Jiang and Haozhun Jin and Denny Jin and Shino Jomoto and Billie Jonn and Heewoo Jun and Tomer Kaftan and Łukasz Kaiser and Ali Kamali and Ingmar Kanitscheider and Nitish Shirish Keskar and Tabarak Khan and Logan Kilpatrick and Jong Wook Kim and Christina Kim and Yongjik Kim and Hendrik Kirchner and Jamie Kiros and Matt Knight and Daniel Kokotajlo and Łukasz Kondraciuk and Andrew Kondrich and Aris Konstantinidis and Kyle Kosic and Gretchen Krueger and Vishal Kuo and Michael Lampe and Ikai Lan and Teddy Lee and Jan Leike and Jade Leung and Daniel Levy and Chak Ming Li and Rachel Lim and Molly Lin and Stephanie Lin and Mateusz Litwin and Theresa Lopez and Ryan Lowe and Patricia Lue and Anna Makanju and Kim Malfacini and Sam Manning and Todor Markov and Yaniv Markovski and Bianca Martin and Katie Mayer and Andrew Mayne and Bob McGrew and Scott Mayer McKinney and Christine McLeavey and Paul McMillan and Jake McNeil and David Medina and Aalok Mehta and Jacob Menick and Luke Metz and Andrey Mishchenko and Pamela Mishkin and Vinnie Monaco and Evan Morikawa and Daniel Mossing and Tong Mu and Mira Murati and Oleg Murk and David Mély and Ashvin Nair and Reiichiro Nakano and Rajeev Nayak and Arvind Neelakantan and Richard Ngo and Hyeonwoo Noh and Long Ouyang and Cullen O'Keefe and Jakub Pachocki and Alex Paino and Joe Palermo and Ashley Pantuliano and Giambattista Parascandolo and Joel Parish and Emy Parparita and Alex Passos and Mikhail Pavlov and Andrew Peng and Adam Perelman and Filipe de Avila Belbute Peres and Michael Petrov and Henrique Ponde de Oliveira Pinto and Michael and Pokorny and Michelle Pokrass and Vitchyr Pong and Tolly Powell and Alethea Power and Boris Power and Elizabeth Proehl and Raul Puri and Alec Radford and Jack Rae and Aditya Ramesh and Cameron Raymond and Francis Real and Kendra Rimbach and Carl Ross and Bob Rotsted and Henri Roussez and Nick Ryder and Mario Saltarelli and Ted Sanders and Shibani Santurkar and Girish Sastry and Heather Schmidt and David Schnurr and John Schulman and Daniel Selsam and Kyla Sheppard and Toki Sherbakov and Jessica Shieh and Sarah Shoker and Pranav Shyam and Szymon Sidor and Eric Sigler and Maddie Simens and Jordan Sitkin and Katarina Slama and Ian Sohl and Benjamin Sokolowsky and Yang Song and Natalie Staudacher and Felipe Petroski Such and Natalie Summers and Ilya Sutskever and Jie Tang and Nikolas Tezak and Madeleine Thompson and Phil Tillet and Amin Tootoonchian and Elizabeth Tseng and Preston Tuggle and Nick Turley and Jerry Tworek and Juan Felipe Cerón Uribe and Andrea Vallone and Arun Vijayvergiya and Chelsea Voss and Carroll Wainwright and Justin Jay Wang and Alvin Wang and Ben Wang and Jonathan Ward and Jason Wei and CJ Weinmann and Akila Welihinda and Peter Welinder and Jiayi Weng and Lilian Weng and Matt Wiethoff and Dave Willner and Clemens Winter and Samuel Wolrich and Hannah Wong and Lauren Workman and Sherwin Wu and Jeff Wu and Michael Wu and Kai Xiao and Tao Xu and Sarah Yoo and Kevin Yu and Qiming Yuan and Wojciech Zaremba and Rowan Zellers and Chong Zhang and Marvin Zhang and Shengjia Zhao and Tianhao Zheng and Juntang Zhuang and William Zhuk and Barret Zoph},
      year={2023},
      eprint={2303.08774},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@inproceedings{brown2020language,
 author = {Brown, Tom and Mann, Benjamin and Ryder, Nick and Subbiah, Melanie and Kaplan, Jared D and Dhariwal, Prafulla and Neelakantan, Arvind and Shyam, Pranav and Sastry, Girish and Askell, Amanda and Agarwal, Sandhini and Herbert-Voss, Ariel and Krueger, Gretchen and Henighan, Tom and Child, Rewon and Ramesh, Aditya and Ziegler, Daniel and Wu, Jeffrey and Winter, Clemens and Hesse, Chris and Chen, Mark and Sigler, Eric and Litwin, Mateusz and Gray, Scott and Chess, Benjamin and Clark, Jack and Berner, Christopher and McCandlish, Sam and Radford, Alec and Sutskever, Ilya and Amodei, Dario},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
 pages = {1877--1901},
 publisher = {Curran Associates, Inc.},
 title = {Language Models are Few-Shot Learners},
 url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf},
 volume = {33},
 year = {2020}
}

@inproceedings{lewis-etal-2020-bart,
    title = "{BART}: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension",
    author = "Lewis, Mike  and
      Liu, Yinhan  and
      Goyal, Naman  and
      Ghazvininejad, Marjan  and
      Mohamed, Abdelrahman  and
      Levy, Omer  and
      Stoyanov, Veselin  and
      Zettlemoyer, Luke",
    editor = "Jurafsky, Dan  and
      Chai, Joyce  and
      Schluter, Natalie  and
      Tetreault, Joel",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2020.acl-main.703",
    doi = "10.18653/v1/2020.acl-main.703",
    pages = "7871--7880",
}

@article{ding2023parameter,
  title={Parameter-efficient fine-tuning of large-scale pre-trained language models},
  author={Ding, Ning and Qin, Yujia and Yang, Guang and Wei, Fuchao and Yang, Zonghan and Su, Yusheng and Hu, Shengding and Chen, Yulin and Chan, Chi-Min and Chen, Weize and others},
  journal={Nature Machine Intelligence},
  volume={5},
  number={3},
  pages={220--235},
  year={2023},
  publisher={Nature Publishing Group UK London}
}

@article{Liu2021P-TuningV2P,
  author    = {Xiao Liu and
               Kaixuan Ji and
               Yicheng Fu and
               Zhengxiao Du and
               Zhilin Yang and
               Jie Tang},
  title     = {P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally
               Across Scales and Tasks},
  journal   = {CoRR},
  volume    = {abs/2110.07602},
  year      = {2021},
  url       = {https://arxiv.org/abs/2110.07602},
  eprinttype = {arXiv},
  eprint    = {2110.07602},
  timestamp = {Fri, 22 Oct 2021 13:33:09 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2110-07602.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{wolf-etal-2020-transformers,
    title = "Transformers: State-of-the-Art Natural Language Processing",
    author = "Thomas Wolf and Lysandre Debut and Victor Sanh and Julien Chaumond and Clement Delangue and Anthony Moi and Pierric Cistac and Tim Rault and Rémi Louf and Morgan Funtowicz and Joe Davison and Sam Shleifer and Patrick von Platen and Clara Ma and Yacine Jernite and Julien Plu and Canwen Xu and Teven Le Scao and Sylvain Gugger and Mariama Drame and Quentin Lhoest and Alexander M. Rush",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
    month = oct,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.emnlp-demos.6",
    pages = "38--45"
}

@inproceedings{
rame2022diverse,
title={Diverse Weight Averaging for Out-of-Distribution Generalization},
author={Alexandre Rame and Matthieu Kirchmeyer and Thibaud Rahier and Alain Rakotomamonjy and patrick gallinari and Matthieu Cord},
booktitle={Advances in Neural Information Processing Systems},
editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
year={2022},
url={https://openreview.net/forum?id=tq_J_MqB3UB}
}

@inproceedings{
yang2022inducing,
title={Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network?},
author={Yibo Yang and Shixiang Chen and Xiangtai Li and Liang Xie and Zhouchen Lin and Dacheng Tao},
booktitle={Advances in Neural Information Processing Systems},
editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
year={2022},
url={https://openreview.net/forum?id=A6EmxI3_Xc}
}


@InProceedings{pmlr-v139-summers21a,
  title = 	 {Nondeterminism and Instability in Neural Network Optimization},
  author =       {Summers, Cecilia and Dinneen, Michael J.},
  booktitle = 	 {Proceedings of the 38th International Conference on Machine Learning},
  pages = 	 {9913--9922},
  year = 	 {2021},
  editor = 	 {Meila, Marina and Zhang, Tong},
  volume = 	 {139},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {18--24 Jul},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v139/summers21a/summers21a.pdf},
  url = 	 {https://proceedings.mlr.press/v139/summers21a.html},

}

@article{bouthillier2021accounting,
  title={Accounting for variance in machine learning benchmarks},
  author={Bouthillier, Xavier and Delaunay, Pierre and Bronzi, Mirko and Trofimov, Assya and Nichyporuk, Brennan and Szeto, Justin and Mohammadi Sepahvand, Nazanin and Raff, Edward and Madan, Kanika and Voleti, Vikram and others},
  journal={Proceedings of Machine Learning and Systems},
  volume={3},
  pages={747--769},
  year={2021}
}

@article{masegosa2020learning,
  title={Learning under model misspecification: Applications to variational and ensemble methods},
  author={Masegosa, Andres},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  pages={5479--5491},
  year={2020}
}

@inproceedings{madhyastha-jain-2019-model,
    title = "On Model Stability as a Function of Random Seed",
    author = "Madhyastha, Pranava  and
      Jain, Rishabh",
    editor = "Bansal, Mohit  and
      Villavicencio, Aline",
    booktitle = "Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/K19-1087",
    doi = "10.18653/v1/K19-1087",
    pages = "929--939",
}

@article{jordan2023calibrated,
  title={Calibrated Chaos: Variance Between Runs of Neural Network Training is Harmless and Inevitable},
  author={Jordan, Keller},
  journal={arXiv preprint arXiv:2304.01910},
  year={2023}}

@article{alquier2016properties,
  title={On the properties of variational approximations of Gibbs posteriors},
  author={Alquier, Pierre and Ridgway, James and Chopin, Nicolas},
  journal={The Journal of Machine Learning Research},
  volume={17},
  number={1},
  pages={8374--8414},
  year={2016},
  publisher={JMLR. org}
}

@article{zhou2022all,
  title={Are all losses created equal: A neural collapse perspective},
  author={Zhou, Jinxin and You, Chong and Li, Xiao and Liu, Kangning and Liu, Sheng and Qu, Qing and Zhu, Zhihui},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={31697--31710},
  year={2022}
}

@inproceedings{
galanti2022on,
title={On the Role of Neural Collapse in Transfer Learning},
author={Tomer Galanti and Andr{\'a}s Gy{\"o}rgy and Marcus Hutter},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=SwIp410B6aQ}
}

@misc{hayou2024lora,
      title={LoRA+: Efficient Low Rank Adaptation of Large Models},
      author={Soufiane Hayou and Nikhil Ghosh and Bin Yu},
      year={2024},
      eprint={2402.12354},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

@misc{jang2024lora,
      title={LoRA Training in the NTK Regime has No Spurious Local Minima},
      author={Uijeong Jang and Jason D. Lee and Ernest K. Ryu},
      year={2024},
      eprint={2402.11867},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}


@InProceedings{pmlr-v202-rangamani23a,
  title = 	 {Feature learning in deep classifiers through Intermediate Neural Collapse},
  author =       {Rangamani, Akshay and Lindegaard, Marius and Galanti, Tomer and Poggio, Tomaso A},
  booktitle = 	 {Proceedings of the 40th International Conference on Machine Learning},
  pages = 	 {28729--28745},
  year = 	 {2023},
  editor = 	 {Krause, Andreas and Brunskill, Emma and Cho, Kyunghyun and Engelhardt, Barbara and Sabato, Sivan and Scarlett, Jonathan},
  volume = 	 {202},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {23--29 Jul},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v202/rangamani23a/rangamani23a.pdf},
  url = 	 {https://proceedings.mlr.press/v202/rangamani23a.html},
  abstract = 	 {In this paper, we conduct an empirical study of the feature learning process in deep classifiers. Recent research has identified a training phenomenon called Neural Collapse (NC), in which the top-layer feature embeddings of samples from the same class tend to concentrate around their means, and the top layer’s weights align with those features. Our study aims to investigate if these properties extend to intermediate layers. We empirically study the evolution of the covariance and mean of representations across different layers and show that as we move deeper into a trained neural network, the within-class covariance decreases relative to the between-class covariance. Additionally, we find that in the top layers, where the between-class covariance is dominant, the subspace spanned by the class means aligns with the subspace spanned by the most significant singular vector components of the weight matrix in the corresponding layer. Finally, we discuss the relationship between NC and Associative Memories (Willshaw et. al. 1969).}
}

@inproceedings{
littwin2023adaptive,
title={Adaptive Optimization in the \${\textbackslash}infty\$-Width Limit},
author={Etai Littwin and Greg Yang},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=zgVDqw9ZUES}
}
@misc{dettmers2023qlora,
      title={QLoRA: Efficient Finetuning of Quantized LLMs},
      author={Tim Dettmers and Artidoro Pagnoni and Ari Holtzman and Luke Zettlemoyer},
      year={2023},
      eprint={2305.14314},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

@inproceedings{kopiczko2023vera,
title={VeRA: Vector-based Random Matrix Adaptation},
author={Dawid J. Kopiczko and Tijmen Blankevoort and Yuki M. Asano},
booktitle={International Conference on Learning Representations},
year={2024},
}

@inproceedings{
li2024loftq,
title={LoftQ: Lo{RA}-Fine-Tuning-aware Quantization for Large Language Models},
author={Yixiao Li and Yifan Yu and Chen Liang and Nikos Karampatziakis and Pengcheng He and Weizhu Chen and Tuo Zhao},
booktitle={The Twelfth International Conference on Learning Representations},
year={2024},
url={https://openreview.net/forum?id=LzPWWPAdY4}
}

@misc{
liu2020roberta,
title={Ro{\{}BERT{\}}a: A Robustly Optimized {\{}BERT{\}} Pretraining Approach},
author={Yinhan Liu and Myle Ott and Naman Goyal and Jingfei Du and Mandar Joshi and Danqi Chen and Omer Levy and Mike Lewis and Luke Zettlemoyer and Veselin Stoyanov},
year={2020},
url={https://openreview.net/forum?id=SyxS0T4tvS}
}

@article{
papyan2020prevalence,
author = {Vardan Papyan  and X. Y. Han  and David L. Donoho },
title = {Prevalence of neural collapse during the terminal phase of deep learning training},
journal = {Proceedings of the National Academy of Sciences},
volume = {117},
number = {40},
pages = {24652-24663},
year = {2020},
doi = {10.1073/pnas.2015509117},
URL = {https://www.pnas.org/doi/abs/10.1073/pnas.2015509117},
eprint = {https://www.pnas.org/doi/pdf/10.1073/pnas.2015509117},
abstract = {Modern practice for training classification deepnets involves a terminal phase of training (TPT), which begins at the epoch where training error first vanishes. During TPT, the training error stays effectively zero, while training loss is pushed toward zero. Direct measurements of TPT, for three prototypical deepnet architectures and across seven canonical classification datasets, expose a pervasive inductive bias we call neural collapse (NC), involving four deeply interconnected phenomena. (NC1) Cross-example within-class variability of last-layer training activations collapses to zero, as the individual activations themselves collapse to their class means. (NC2) The class means collapse to the vertices of a simplex equiangular tight frame (ETF). (NC3) Up to rescaling, the last-layer classifiers collapse to the class means or in other words, to the simplex ETF (i.e., to a self-dual configuration). (NC4) For a given activation, the classifier’s decision collapses to simply choosing whichever class has the closest train class mean (i.e., the nearest class center [NCC] decision rule). The symmetric and very simple geometry induced by the TPT confers important benefits, including better generalization performance, better robustness, and better interpretability.}}

@article{papyan2020traces,
  author  = {Vardan Papyan},
  title   = {Traces of Class/Cross-Class Structure Pervade Deep Learning Spectra},
  journal = {Journal of Machine Learning Research},
  year    = {2020},
  volume  = {21},
  number  = {252},
  pages   = {1--64},
  url     = {http://jmlr.org/papers/v21/20-933.html}
}

@inproceedings{
chen2023which,
title={Which Layer is Learning Faster? A Systematic Exploration of Layer-wise Convergence Rate for Deep Neural Networks},
author={Yixiong Chen and Alan Yuille and Zongwei Zhou},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=wlMDF1jQF86}
}
@article{hou2022closer,
  title={A closer look at prototype classifier for few-shot image classification},
  author={Hou, Mingcheng and Sato, Issei},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={25767--25778},
  year={2022}
}

@article{malladi2024fine,
  title={Fine-tuning language models with just forward passes},
  author={Malladi, Sadhika and Gao, Tianyu and Nichani, Eshaan and Damian, Alex and Lee, Jason D and Chen, Danqi and Arora, Sanjeev},
  journal={Advances in Neural Information Processing Systems},
  volume={36},
  year={2024}
}

@inproceedings{fu2023effectiveness,
  title={On the effectiveness of parameter-efficient fine-tuning},
  author={Fu, Zihao and Yang, Haoran and So, Anthony Man-Cho and Lam, Wai and Bing, Lidong and Collier, Nigel},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={37},
  pages={12799--12807},
  year={2023}
}

@article{kim2020adjusting,
  title={Adjusting decision boundary for class imbalanced learning},
  author={Kim, Byungju and Kim, Junmo},
  journal={IEEE Access},
  volume={8},
  pages={81674--81685},
  year={2020},
  publisher={IEEE}
}

}
@article{kumar2022fine,
  title={Fine-tuning can distort pretrained features and underperform out-of-distribution},
  author={Kumar, Ananya and Raghunathan, Aditi and Jones, Robbie and Ma, Tengyu and Liang, Percy},
  journal={arXiv preprint arXiv:2202.10054},
  year={2022}
}

@inproceedings{
trivedi2023a,
title={A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias},
author={Puja Trivedi and Danai Koutra and Jayaraman J. Thiagarajan},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=wkg_b4-IwTZ}
}

@inproceedings{
kirichenko2023last,
title={Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations},
author={Polina Kirichenko and Pavel Izmailov and Andrew Gordon Wilson},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=Zb6c8A-Fghk}
}

@inproceedings{wei2022more,
  title = {More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize},
  author = {Wei, Alexander and Hu, Wei and Steinhardt, Jacob},
  booktitle = {Proceedings of the 39th International Conference on Machine Learning},
  year = {2022}
}

@misc{
mohamadi2023a,
title={A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel},
author={Mohamad Amin Mohamadi and Danica J. Sutherland},
year={2023},
url={https://openreview.net/forum?id=HN0ehX-ov5Q}
}

@article{shah2020pitfalls,
  title={The Pitfalls of Simplicity Bias in Neural Networks},
  author={Shah, Harshay and Tamuly, Kaustav and Raghunathan, Aditi and Jain, Prateek and Netrapalli, Praneeth},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  year={2020}
}

@inproceedings{
nguyen2021do,
title={Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth},
author={Thao Nguyen and Maithra Raghu and Simon Kornblith},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=KJNcAkY8tY4}
}


@article{chizat2019lazy,
  title={On lazy training in differentiable programming},
  author={Chizat, Lenaic and Oyallon, Edouard and Bach, Francis},
  journal={Advances in neural information processing systems},
  volume={32},
  year={2019}
}

@inproceedings{malladi2023kernel,
  title={A kernel-based view of language model fine-tuning},
  author={Malladi, Sadhika and Wettig, Alexander and Yu, Dingli and Chen, Danqi and Arora, Sanjeev},
  booktitle={International Conference on Machine Learning},
  pages={23610--23641},
  year={2023},
  organization={PMLR}
}

@article{chen2024analyzing,
  title={Analyzing Generalization of Neural Networks through Loss Path Kernels},
  author={Chen, Yilan and Huang, Wei and Wang, Hao and Loh, Charlotte and Srivastava, Akash and Nguyen, Lam and Weng, Lily},
  journal={Advances in Neural Information Processing Systems},
  volume={36},
  year={2024}
}
@inproceedings{
ren2023how,
title={How to prepare your task head for finetuning},
author={Yi Ren and Shangmin Guo and Wonho Bae and Danica J. Sutherland},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=gVOXZproe-e}
}
@inproceedings{ha2024domain,
  title={Domain-Aware Fine-Tuning: Enhancing Neural Network Adaptability},
  author={Ha, Seokhyeon and Jeong, Sunbeom and Lee, Jungwoo},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={38},
  pages={12261--12269},
  year={2024}
}
@misc{ren2022better,
      title={Better Supervisory Signals by Observing Learning Paths},
      author={Yi Ren and Shangmin Guo and Danica J. Sutherland},
      year={2022},
      eprint={2203.02485},
      archivePrefix={arXiv},
      primaryClass={stat.ML}
}

@article{
agarwala2023temperature,
title={Temperature check: theory and practice for training models with softmax-cross-entropy losses},
author={Atish Agarwala and Samuel Stern Schoenholz and Jeffrey Pennington and Yann Dauphin},
journal={Transactions on Machine Learning Research},
issn={2835-8856},
year={2023},
url={https://openreview.net/forum?id=LBA2Jj5Gqn},
note={}
}

@inproceedings{kornblith2019better,
  title={Do better imagenet models transfer better?},
  author={Kornblith, Simon and Shlens, Jonathon and Le, Quoc V},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={2661--2671},
  year={2019}
}

@inproceedings{zhang2020side,
  title={Side-tuning: a baseline for network adaptation via additive side networks},
  author={Zhang, Jeffrey O and Sax, Alexander and Zamir, Amir and Guibas, Leonidas and Malik, Jitendra},
  booktitle={Computer Vision--ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020, Proceedings, Part III 16},
  pages={698--714},
  year={2020},
  organization={Springer}
}
@article{jiang2019smart,
  title={Smart: Robust and efficient fine-tuning for pre-trained natural language models through principled regularized optimization},
  author={Jiang, Haoming and He, Pengcheng and Chen, Weizhu and Liu, Xiaodong and Gao, Jianfeng and Zhao, Tuo},
  journal={arXiv preprint arXiv:1911.03437},
  year={2019}
}

@article{tripuraneni2020theory,
  title={On the theory of transfer learning: The importance of task diversity},
  author={Tripuraneni, Nilesh and Jordan, Michael and Jin, Chi},
  journal={Advances in neural information processing systems},
  volume={33},
  pages={7852--7862},
  year={2020}
}

@article{zhuang2020comprehensive,
  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},
  journal={Proceedings of the IEEE},
  volume={109},
  number={1},
  pages={43--76},
  year={2020},
  publisher={IEEE}
}

@article{lee2019wide,
  title={Wide neural networks of any depth evolve as linear models under gradient descent},
  author={Lee, Jaehoon and Xiao, Lechao and Schoenholz, Samuel and Bahri, Yasaman and Novak, Roman and Sohl-Dickstein, Jascha and Pennington, Jeffrey},
  journal={Advances in neural information processing systems},
  volume={32},
  year={2019}
}

@article{arora2019exact,
  title={On exact computation with an infinitely wide neural net},
  author={Arora, Sanjeev and Du, Simon S and Hu, Wei and Li, Zhiyuan and Salakhutdinov, Russ R and Wang, Ruosong},
  journal={Advances in neural information processing systems},
  volume={32},
  year={2019}
}

@article{muller2019does,
  title={When does label smoothing help?},
  author={M{\"u}ller, Rafael and Kornblith, Simon and Hinton, Geoffrey E},
  journal={Advances in neural information processing systems},
  volume={32},
  year={2019}
}

@article{pereyra2017regularizing,
  title={Regularizing neural networks by penalizing confident output distributions},
  author={Pereyra, Gabriel and Tucker, George and Chorowski, Jan and Kaiser, {\L}ukasz and Hinton, Geoffrey},
  journal={arXiv preprint arXiv:1701.06548},
  year={2017}
}

@inproceedings{
galanti2022on,
title={On the Role of Neural Collapse in Transfer Learning},
author={Tomer Galanti and Andr{\'a}s Gy{\"o}rgy and Marcus Hutter},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=SwIp410B6aQ}
}

@inproceedings{
yang2024feature,
title={Feature Learning in Infinite Depth Neural Networks},
author={Greg Yang and Dingli Yu and Chen Zhu and Soufiane Hayou},
booktitle={The Twelfth International Conference on Learning Representations},
year={2024},
url={https://openreview.net/forum?id=17pVDnpwwl}
}

@article{neyshabur2020being,
  title={What is being transferred in transfer learning?},
  author={Neyshabur, Behnam and Sedghi, Hanie and Zhang, Chiyuan},
  journal={Advances in neural information processing systems},
  volume={33},
  pages={512--523},
  year={2020}
}

@inproceedings{maini2023neural,
      title={Can Neural Network Memorization Be Localized?},
      author={Pratyush Maini and Michael C. Mozer and Hanie Sedghi and Zachary C. Lipton and J. Zico Kolter and Chiyuan Zhang},
      year={2023},
  editor       = {Andreas Krause and
                  Emma Brunskill and
                  Kyunghyun Cho and
                  Barbara Engelhardt and
                  Sivan Sabato and
                  Jonathan Scarlett},
  booktitle    = {International Conference on Machine Learning, {ICML} 2023, 23-29 July
                  2023, Honolulu, Hawaii, {USA}},
  series       = {Proceedings of Machine Learning Research},
  volume       = {202},
  pages        = {23536--23557},
  publisher    = {{PMLR}},
  year         = {2023},
  url          = {https://proceedings.mlr.press/v202/maini23a.html},
  timestamp    = {Mon, 28 Aug 2023 17:23:08 +0200},
  biburl       = {https://dblp.org/rec/conf/icml/MainiMSLKZ23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{
soudry2018the,
title={The Implicit Bias of Gradient Descent on Separable Data},
author={Daniel Soudry and Elad Hoffer and Nathan Srebro},
booktitle={International Conference on Learning Representations},
year={2018},
url={https://openreview.net/forum?id=r1q7n9gAb},
}

@inproceedings{rudner2019natural,
  title={The natural neural tangent kernel: Neural network training dynamics under natural gradient descent},
  author={Rudner, Tim GJ and Wenzel, Florian and Teh, Yee Whye and Gal, Yarin},
  booktitle={4th workshop on Bayesian Deep Learning (NeurIPS 2019)},
  year={2019}
}

@misc{ji2019risk,
      title={Risk and parameter convergence of logistic regression},
      author={Ziwei Ji and Matus Telgarsky},
      year={2019},
      eprint={1803.07300},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}


@misc{fort2020deep,
      title={Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel},
      author={Stanislav Fort and Gintare Karolina Dziugaite and Mansheej Paul and Sepideh Kharaghani and Daniel M. Roy and Surya Ganguli},
      year={2020},
      eprint={2010.15110},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

@inproceedings{johnson1984extensions,
  title={Extensions of Lipschitz mappings into a Hilbert space. Conference in modern analysis and probability (New Haven, Conn., 1982), 189--206},
  author={Johnson, William B and Lindenstrauss, Joram},
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}

@inproceedings{
zeng2024the,
title={The Expressive Power of Low-Rank Adaptation},
author={Yuchen Zeng and Kangwook Lee},
booktitle={The Twelfth International Conference on Learning Representations},
year={2024},
url={https://openreview.net/forum?id=likXVjmh3E}
}


@InProceedings{pmlr-v196-ben-shaul22a,
  title = 	 {Nearest Class-Center Simplification through Intermediate Layers},
  author =       {Ben-Shaul, Ido and Dekel, Shai},
  booktitle = 	 {Proceedings of Topological, Algebraic, and Geometric Learning Workshops 2022},
  pages = 	 {37--47},
  year = 	 {2022},
  editor = 	 {Cloninger, Alexander and Doster, Timothy and Emerson, Tegan and Kaul, Manohar and Ktena, Ira and Kvinge, Henry and Miolane, Nina and Rieck, Bastian and Tymochko, Sarah and Wolf, Guy},
  volume = 	 {196},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {25 Feb--22 Jul},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v196/ben-shaul22a/ben-shaul22a.pdf},
  url = 	 {https://proceedings.mlr.press/v196/ben-shaul22a.html},
  abstract = 	 {Recent advances in neural network theory have introduced geometric properties that occur during training, past the Interpolation Threshold- where the training error reaches zero. We inquire into the phenomena coined \emph{Neural Collapse} in the intermediate layers of the network, and emphasize the innerworkings of Nearest Class-Center Mismatch inside a deepnet. We further show that these processes occur both in vision and language model architectures. Lastly, we propose a Stochastic Variability-Simplification Loss (SVSL) that encourages better geometrical features in intermediate layers, yielding improvements in both train metrics and generalization.}
}
@article{yuan2023revisiting,
      title={Revisiting Out-of-distribution Robustness in NLP: Benchmark, Analysis, and LLMs Evaluations},
      author={Yuan, Lifan and Chen, Yangyi and Cui, Ganqu and Gao, Hongcheng and Zou, Fangyuan and Cheng, Xingyi and Ji, Heng and Liu, Zhiyuan and Sun, Maosong},
      journal={arXiv preprint arXiv:2306.04618},
      year={2023}
}

@misc{dernoncourt2017pubmed,
      title={PubMed 200k RCT: a Dataset for Sequential Sentence Classification in Medical Abstracts},
      author={Franck Dernoncourt and Ji Young Lee},
      year={2017},
      eprint={1710.06071},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@misc{mixon2020neural,
      title={Neural collapse with unconstrained features},
      author={Dustin G. Mixon and Hans Parshall and Jianzong Pi},
      year={2020},
      eprint={2011.11619},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

@article{Fang_2021,
   title={Exploring deep neural networks via layer-peeled model: Minority collapse in imbalanced training},
   volume={118},
   ISSN={1091-6490},
   url={http://dx.doi.org/10.1073/pnas.2103091118},
   DOI={10.1073/pnas.2103091118},
   number={43},
   journal={Proceedings of the National Academy of Sciences},
   publisher={Proceedings of the National Academy of Sciences},
   author={Fang, Cong and He, Hangfeng and Long, Qi and Su, Weijie J.},
   year={2021},
   month=oct }

@article{radford2019language,
  title={Language models are unsupervised multitask learners},
  author={Radford, Alec and Wu, Jeffrey and Child, Rewon and Luan, David and Amodei, Dario and Sutskever, Ilya and others},
  journal={OpenAI blog},
  volume={1},
  number={8},
  pages={9},
  year={2019}
}

@inproceedings{socher-etal-2013-recursive,
    title = "Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank",
    author = "Socher, Richard  and
      Perelygin, Alex  and
      Wu, Jean  and
      Chuang, Jason  and
      Manning, Christopher D.  and
      Ng, Andrew  and
      Potts, Christopher",
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    year = "2013",
}

@inproceedings{nakov-etal-2016-semeval,
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      Rosenthal, Sara  and
      Sebastiani, Fabrizio  and
      Stoyanov, Veselin",
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    year = "2016",
}

@inproceedings{potts-etal-2021-dynasent,
    title = "{D}yna{S}ent: A Dynamic Benchmark for Sentiment Analysis",
    author = "Potts, Christopher  and
      Wu, Zhengxuan  and
      Geiger, Atticus  and
      Kiela, Douwe",
    booktitle = "Proceedings of ACL-IJCNLP",
    year = "2021",
}

@inproceedings{mcAuley2013hidden,
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    booktitle = {Proceedings of ACM Conference on Recommender Systems},
}

@article{warstadt-etal-2019-neural,
    title = "Neural Network Acceptability Judgments",
    author = "Warstadt, Alex  and
      Singh, Amanpreet  and
      Bowman, Samuel R.",
    editor = "Lee, Lillian  and
      Johnson, Mark  and
      Roark, Brian  and
      Nenkova, Ani",
    journal = "Transactions of the Association for Computational Linguistics",
    volume = "7",
    year = "2019",
    address = "Cambridge, MA",
    publisher = "MIT Press",
    url = "https://aclanthology.org/Q19-1040",
    doi = "10.1162/tacl_a_00290",
    pages = "625--641",
  }

@inproceedings{dolan2005automatically,
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  year={2005}
}
@inproceedings{clark-etal-2019-boolq,
    title = "{B}ool{Q}: Exploring the Surprising Difficulty of Natural Yes/No Questions",
    author = "Clark, Christopher  and
      Lee, Kenton  and
      Chang, Ming-Wei  and
      Kwiatkowski, Tom  and
      Collins, Michael  and
      Toutanova, Kristina",
    editor = "Burstein, Jill  and
      Doran, Christy  and
      Solorio, Thamar",
    booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/N19-1300",
    doi = "10.18653/v1/N19-1300",
    pages = "2924--2936",
}

@inproceedings{de2019commitmentbank,
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  volume={23},
  pages={107--124},
  year={2019}
}

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  year={2005},
  organization={Springer}
}
@article{rte2,
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month = {01},
pages = {},
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}
@inproceedings{giampiccolo2007third,
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  year={2007}
}

@article{bentivogli2009fifth,
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}

@inproceedings{burstein2019proceedings,
  title={Proceedings of the 2019 conference of the north american chapter of the association for computational linguistics: Human language technologies, volume 1 (long and short papers)},
  author={Burstein, Jill and Doran, Christy and Solorio, Thamar},
  booktitle={Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)},
  year={2019}
}

@inproceedings{levesque2012winograd,
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}

@article{scikit-learn,
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@misc{kingma2017adam,
      title={Adam: A Method for Stochastic Optimization},
      author={Diederik P. Kingma and Jimmy Ba},
      year={2017},
      eprint={1412.6980},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

@misc{paszke2019pytorch,
      title={PyTorch: An Imperative Style, High-Performance Deep Learning Library},
      author={Adam Paszke and Sam Gross and Francisco Massa and Adam Lerer and James Bradbury and Gregory Chanan and Trevor Killeen and Zeming Lin and Natalia Gimelshein and Luca Antiga and Alban Desmaison and Andreas Köpf and Edward Yang and Zach DeVito and Martin Raison and Alykhan Tejani and Sasank Chilamkurthy and Benoit Steiner and Lu Fang and Junjie Bai and Soumith Chintala},
      year={2019},
      eprint={1912.01703},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

@Misc{functorch2021,
  author =       {Horace He, Richard Zou},
  title =        {functorch: JAX-like composable function transforms for PyTorch},
  howpublished = {\url{https://github.com/pytorch/functorch}},
  year =         {2021}
}


@InProceedings{pmlr-v162-novak22a,
  title = 	 {Fast Finite Width Neural Tangent Kernel},
  author =       {Novak, Roman and Sohl-Dickstein, Jascha and Schoenholz, Samuel S},
  booktitle = 	 {Proceedings of the 39th International Conference on Machine Learning},
  pages = 	 {17018--17044},
  year = 	 {2022},
  editor = 	 {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan},
  volume = 	 {162},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {17--23 Jul},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v162/novak22a/novak22a.pdf},
  url = 	 {https://proceedings.mlr.press/v162/novak22a.html},
  }

@article{fisher1936use,
  title={The use of multiple measurements in taxonomic problems},
  author={Fisher, Ronald A},
  journal={Annals of eugenics},
  volume={7},
  number={2},
  pages={179--188},
  year={1936},
  publisher={Wiley Online Library}
}
