publications | Baris Askin

Also available on Google Scholar. (* denotes equal contribution.)

2026

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

2026, Preprint, under review

@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},
}

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

@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}
}

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

2026, Preprint, under review

arXiv Bib

@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},
}

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

2026, Preprint, under review

arXiv Bib

@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},
}

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

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

2026, Preprint, under review

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},
}

2025

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}
}

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

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},
}

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

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

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"
}

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

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},
}

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},
}