publications

2026

1. NeurIPS ICML FoGen

   

   Emergent and Subliminal Misalignment Through the Lens of Data-Mediated Transfer

   B. Askin^*, M. Ustaomeroglu^*, A. Nayak^*, G. Joshi, G. Qu, and C. Joe-Wong

   In Conference on Neural Information Processing Systems (NeurIPS), 2026

   arXiv Bib

   @misc{askin2026emergentsubliminalmisalignmentlens,
         title={Emergent and Subliminal Misalignment Through the Lens of Data-Mediated Transfer},
         author={Baris Askin and Muhammed Ustaomeroglu and Anupam Nayak and Gauri Joshi and Guannan Qu and Carlee Joe-Wong},
         year={2026},
         eprint={2605.12798},
         archivePrefix={arXiv},
         primaryClass={cs.LG},
         url={https://arxiv.org/abs/2605.12798},
   }

2. ICLR

   

   Internal Planning in Language Models: Characterizing Horizon and Branch Awareness

   M. Ustaomeroglu^*, B. Askin^*, G. Joshi, C. Joe-Wong, and G. Qu

   In International Conference on Learning Representations (ICLR), 2026

   arXiv Bib Video Poster

   @inproceedings{
   ustaomeroglu2026internal,
   title={Internal Planning in Language Models: Characterizing Horizon and Branch Awareness},
   author={Muhammed Ustaomeroglu and Baris Askin and Gauri Joshi and Carlee Joe-Wong and Guannan Qu},
   booktitle={The Fourteenth International Conference on Learning Representations},
   year={2026},
   url={https://openreview.net/forum?id=dqGWQdFdTC}
   }

3. NeurIPS

   

   Federate the Router: Learning LM Routers with Sparse and Decentralized Evaluations

   B. Askin^*, S. Patel^*, A. Nayak^*, A. Vigano, J. Woo, G. Joshi, and C. Joe-Wong

   In Conference on Neural Information Processing Systems (NeurIPS), 2026

   arXiv Bib PROJECT PAGE Code

   @misc{askin2026federaterouterlearninglanguage,
         title={Federate the Router: Learning Language Model Routers with Sparse and Decentralized Evaluations},
         author={Baris Askin and Shivam Patel and Anupam Nayak and Andrea Vigano and Jiin Woo and Gauri Joshi and Carlee Joe-Wong},
         year={2026},
         eprint={2601.22318},
         archivePrefix={arXiv},
         primaryClass={cs.LG},
         url={https://arxiv.org/abs/2601.22318},
   }

4. NeurIPS

   

   Reviving Stale Updates: Data-Free Knowledge Distillation for Asynchronous Federated Learning

   B. Askin, H. R. Roth, Z. Sun, C. Joe-Wong, G. Joshi, and Z. Xu

   In Conference on Neural Information Processing Systems (NeurIPS), 2026

   arXiv Bib Code

   @misc{askin2026revivingstaleupdatesdatafree,
         title={Reviving Stale Updates: Data-Free Knowledge Distillation for Asynchronous Federated Learning},
         author={Baris Askin and Holger R. Roth and Zhenyu Sun and Carlee Joe-Wong and Gauri Joshi and Ziyue Xu},
         year={2026},
         eprint={2511.00655},
         archivePrefix={arXiv},
         primaryClass={cs.LG},
         url={https://arxiv.org/abs/2511.00655},
   }

5. ICML RLxF ICML DEMO

   

   PubSwap: Public-Data Off-Policy Coordination for Federated RLVR

   A. Nayak^*, B. Askin^*, M. Ustaomeroglu, C. Joe-Wong, and G. Joshi

   2026, Initial version at ICML 2026 Workshop on RL from World Feedback and ICML 2026 Decision-Making from Offline Datasets to Online Adaptation: Black-Box Optimization to Reinforcement Learning

   arXiv Bib

   @misc{nayak2026pubswappublicdataoffpolicycoordination,
         title={PubSwap: Public-Data Off-Policy Coordination for Federated RLVR},
         author={Anupam Nayak and Baris Askin and Muhammed Ustaomeroglu and Carlee Joe-Wong and Gauri Joshi},
         year={2026},
         eprint={2604.12160},
         archivePrefix={arXiv},
         primaryClass={cs.LG},
         url={https://arxiv.org/abs/2604.12160},
   }

6. Preprint

   

   Aligned Data Can Induce Misalignment via Context Confusion

   Y. Bakman, D. N. Yaldiz, B. Askin, S. Roy, M. Ziyadi, S. Avestimehr, and S. P. Karimireddy

   2026

   arXiv Bib

   @misc{bakman2026context,
     title = {Aligned Data Can Induce Misalignment via Context Confusion},
     author = {Bakman, Y. and Yaldiz, D. N. and Askin, B. and Roy, S. and Ziyadi, M. and Avestimehr, S. and Karimireddy, S. P.},
     year = {2026},
     url = {https://arxiv.org/abs/2609.38379},
   }

7. ICML Position

   

   Position: Federated Learning is a Lens towards a Democratized Future for the Scaling Law Era

   H. H. Jiang, B. Askin, G. Joshi, and C. Joe-Wong

   In International Conference on Machine Learning (ICML) Position Track, 2026

   Link Bib

   @inproceedings{
   jiang2026position,
   title={Position: Federated Learning is a Lens towards a Democratized Future for the Scaling Law Era},
   author={Harry H. Jiang and Baris Askin and Gauri Joshi and Carlee Joe-Wong},
   booktitle={Forty-third International Conference on Machine Learning Position Paper Track},
   year={2026},
   url={https://openreview.net/forum?id=td1fQFeIiI}
   }

2025

1. NeurIPS

   

   Ravan: Multi-Head Low-Rank Adaptation for Federated Fine-Tuning

   A. Raje, B. Askin, D. Jhunjhunwala, and G. Joshi

   In Conference on Neural Information Processing Systems (NeurIPS), 2025

   arXiv Bib

   @article{raje2026ravan,
     title={Ravan: Multi-head low-rank adaptation for federated fine-tuning},
     author={Raje, Arian and Askin, Baris and Jhunjhunwala, Divyansh and Joshi, Gauri},
     journal={Advances in Neural Information Processing Systems},
     volume={38},
     pages={48564--48592},
     year={2026}
   }

2. AISTATS

   

   Federated Communication-Efficient Multi-Objective Optimization

   B. Askin, P. Sharma, G. Joshi, and C. Joe-Wong

   In Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS), May 2025

   arXiv Bib Code Poster

   @inproceedings{askin2025fedcmoo,
     title = {Federated Communication-Efficient Multi-Objective Optimization},
     author = {Askin, B. and Sharma, P. and Joshi, G. and Joe-Wong, C.},
     booktitle = {Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS)},
     pages = {4627--4635},
     year = {2025},
     volume = {258},
     series = {Proceedings of Machine Learning Research},
     month = may,
     publisher = {PMLR},
     url = {https://proceedings.mlr.press/v258/askin25a.html},
   }

2024

1. UAI

   

   FedAST: Federated Asynchronous Simultaneous Training

   B. Askin, P. Sharma, C. Joe-Wong, and G. Joshi

   In Proceedings of the 40th Conference on Uncertainty in Artificial Intelligence (UAI), Jul 2024

   arXiv Bib Code Poster

   @inproceedings{askin2024fedast,
     title = {{FedAST}: Federated Asynchronous Simultaneous Training},
     author = {Askin, B. and Sharma, P. and Joe-Wong, C. and Joshi, G.},
     booktitle = {Proceedings of the 40th Conference on Uncertainty in Artificial Intelligence (UAI)},
     pages = {138--172},
     year = {2024},
     volume = {244},
     series = {Proceedings of Machine Learning Research},
     month = jul,
     publisher = {PMLR},
     url = {https://proceedings.mlr.press/v244/askin24a.html},
   }

2. TMI

   

   DEQ-MPI: A Deep Equilibrium Reconstruction with Learned Consistency for Magnetic Particle Imaging

   A. Güngör, B. Askin, D. A. Soydan, C. B. Top, E. U. Saritas, and T. Çukur

   IEEE Transactions on Medical Imaging, Jan 2024

   Bib Code

   @article{gungor2024deqmpi,
     title = {{DEQ-MPI}: A Deep Equilibrium Reconstruction with Learned Consistency for Magnetic Particle Imaging},
     author = {G{\"u}ng{\"o}r, A. and Askin, B. and Soydan, D. A. and Top, C. B. and Saritas, E. U. and {\c{C}}ukur, T.},
     journal = {IEEE Transactions on Medical Imaging},
     volume = {43},
     number = {1},
     pages = {321--334},
     year = {2024},
     month = jan,
     publisher = {IEEE},
     url = {https://ieeexplore.ieee.org/document/10198492},
   }

2023

1. IJMPI

   

   A Denoiser Scaling Technique for Plug-and-Play MPI Reconstruction

   A. Güngör, B. Askin, D. A. Soydan, E. U. Saritas, C. B. Top, and T. Çukur

   International Journal on Magnetic Particle Imaging (IJMPI), Mar 2023

   Bib

   @article{gungor2023denoiser,
     title = {A Denoiser Scaling Technique for Plug-and-Play {MPI} Reconstruction},
     author = {G{\"u}ng{\"o}r, A. and Askin, B. and Soydan, D. A. and Saritas, E. U. and Top, C. B. and {\c{C}}ukur, T.},
     journal = {International Journal on Magnetic Particle Imaging (IJMPI)},
     volume = {9},
     number = {1 Suppl 1},
     year = {2023},
     month = mar,
     publisher = {Infinite Science Publishing},
     url = {https://www.journal.iwmpi.org/index.php/iwmpi/article/view/636},
   }

2022

1. MLMIR

   

   PP-MPI: A Deep Plug-and-Play Prior for Magnetic Particle Imaging Reconstruction

   B. Askin, A. Güngör, D. A. Soydan, E. U. Saritas, C. B. Top, and T. Çukur

   In Workshop on Machine Learning for Medical Image Reconstruction (MLMIR), 2022

   Link Bib Code

   @InProceedings{10.1007/978-3-031-17247-2_11,
   author="Askin, Baris
   and G{\"u}ng{\"o}r, Alper
   and Alptekin Soydan, Damla
   and Saritas, Emine Ulku
   and Top, Can Bar{\i}{\c{s}}
   and Cukur, Tolga",
   editor="Haq, Nandinee
   and Johnson, Patricia
   and Maier, Andreas
   and Qin, Chen
   and W{\"u}rfl, Tobias
   and Yoo, Jaejun",
   title="PP-MPI: A Deep Plug-and-Play Prior for Magnetic Particle Imaging Reconstruction",
   booktitle="Machine Learning for Medical Image Reconstruction",
   year="2022",
   publisher="Springer International Publishing",
   address="Cham",
   pages="105--114",
   isbn="978-3-031-17247-2"
   }

2. TMI

   

   TranSMS: Transformers for Super-Resolution Calibration in Magnetic Particle Imaging

   A. Güngör, B. Askin, D. A. Soydan, E. U. Saritas, C. B. Top, and T. Çukur

   IEEE Transactions on Medical Imaging, Dec 2022

   Link Bib Code

   @article{gungor2022transms,
     title = {{TranSMS}: Transformers for Super-Resolution Calibration in Magnetic Particle Imaging},
     author = {G{\"u}ng{\"o}r, A. and Askin, B. and Soydan, D. A. and Saritas, E. U. and Top, C. B. and {\c{C}}ukur, T.},
     journal = {IEEE Transactions on Medical Imaging},
     volume = {41},
     number = {12},
     pages = {3562--3574},
     year = {2022},
     month = dec,
     publisher = {IEEE},
     url = {https://ieeexplore.ieee.org/document/9825706},
   }

2021

1. EMBC

   

   Deep Learned Super Resolution of System Matrices for Magnetic Particle Imaging

   A. Güngör, B. Askin, D. A. Soydan, C. B. Top, and T. Çukur

   In Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Nov 2021

   Link Bib

   @inproceedings{gungor2021superresolution,
     title = {Deep Learned Super Resolution of System Matrices for Magnetic Particle Imaging},
     author = {G{\"u}ng{\"o}r, A. and Askin, B. and Soydan, D. A. and Top, C. B. and {\c{C}}ukur, T.},
     booktitle = {Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)},
     pages = {3749--3752},
     year = {2021},
     month = nov,
     publisher = {IEEE},
     url = {https://ieeexplore.ieee.org/document/9630601},
   }

2. SIU

   

   A CNN Based Super-Resolution Technique for Magnetic Particle Imaging System Matrix

   B. Askin, A. Güngör, D. A. Soydan, C. B. Top, and T. Çukur

   In Signal Processing and Communications Applications Conference (SIU), Jun 2021

   Link Bib

   @inproceedings{askin2021cnn,
     title = {A {CNN} Based Super-Resolution Technique for Magnetic Particle Imaging System Matrix},
     author = {Askin, B. and G{\"u}ng{\"o}r, A. and Soydan, D. A. and Top, C. B. and {\c{C}}ukur, T.},
     booktitle = {Signal Processing and Communications Applications Conference (SIU)},
     pages = {1--4},
     year = {2021},
     month = jun,
     publisher = {IEEE},
     url = {https://ieeexplore.ieee.org/document/9477772},
   }