Ömer Faruk Akgül

I am a Ph.D. student in Computer Science at the University of Southern California, advised by Prof. Viktor Prasanna, and I also closely work with Prof. Willie Neiswanger. I received my B.Sc. in Computer Science from Bilkent University. Previously, I worked with Prof. Tudor Dumitras at the University of Maryland on machine learning for security.

My current research interests include:

Language model reasoning
Efficient and reliable machine learning
Post-training and inference-time methods for large language models
Structured reasoning over temporal and relational data

news

Jan 15, 2026	Recipe-TKG is accepted to EACL 2026.
Jun 09, 2025	I started working as an Applied Science Intern at Amazon. I will be working on Text-to-SQL systems.
Aug 15, 2024	Conformal Prediction for Federated Graph Neural Networks with Missing Neighbor Information is accepted to UAI’25!
May 15, 2023	An Efficient Distributed Graph Engine for Deep Learning on Graphs accepted to the SC’23 workshop.
Aug 22, 2022	Started the PhD program in Computer Science at USC, joining Prof. Viktor Prasanna’s research group.
Jun 15, 2021	I’m excited to join UMD MC2 as a summer intern!

publications

LLM

Rethinking RL for LLM Reasoning: It’s Sparse Policy Selection, Not Capability Learning

Ömer Faruk Akgül, Rajgopal Kannan, Willie Neiswanger, and 1 more author

arXiv preprint arXiv:2605.06241, 2026

arXiv Bib

@article{akgul2026rethinking,
  title = {Rethinking RL for LLM Reasoning: It's Sparse Policy Selection, Not Capability Learning},
  author = {Akg{\"u}l, {\"O}mer Faruk and Kannan, Rajgopal and Neiswanger, Willie and Prasanna, Viktor},
  journal = {arXiv preprint arXiv:2605.06241},
  year = {2026},
}

LLM

LYNX: Learning Dynamic Exits for Confidence-Controlled Reasoning

Ömer Faruk Akgül, Yusuf Hakan Kalaycı, Rajgopal Kannan, and 2 more authors

arXiv preprint arXiv:2512.05325, 2025

arXiv Bib

@article{akgul2025lynx,
  title = {LYNX: Learning Dynamic Exits for Confidence-Controlled Reasoning},
  author = {Akg{\"u}l, {\"O}mer Faruk and Kalayc{\i}, Yusuf Hakan and Kannan, Rajgopal and Neiswanger, Willie and Prasanna, Viktor},
  journal = {arXiv preprint arXiv:2512.05325},
  year = {2025},
}

T2SQL

Schema-Free Text-to-SQL: Learning Enterprise Database Structure from Query Logs

Ömer Faruk Akgül, Nikhil Kapahi, and Prajit Muppidi

arXiv preprint, 2026

Bib

@article{akgul2026schemafree,
  title = {Schema-Free Text-to-SQL: Learning Enterprise Database Structure from Query Logs},
  author = {Akg{\"u}l, {\"O}mer Faruk and Kapahi, Nikhil and Muppidi, Prajit},
  journal = {arXiv preprint},
  year = {2026},
}

RAG

SPARC-RAG: Adaptive Sequential-Parallel Scaling with Context Management for Retrieval-Augmented Generation

Yuxin Yang, Gangda Deng, Ömer Faruk Akgül, and 6 more authors

In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL), 2026

arXiv Bib

@inproceedings{yang2026sparcrag,
  title = {SPARC-RAG: Adaptive Sequential-Parallel Scaling with Context Management for Retrieval-Augmented Generation},
  author = {Yang, Yuxin and Deng, Gangda and Akg{\"u}l, {\"O}mer Faruk and Chitsazan, Nima and Govilkar, Yash and Tigalappanavara, Akasha and Zhang, Shi-Xiong and Sahu, Sambit and Prasanna, Viktor},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL)},
  year = {2026},
}

GNN

Training Diverse Graph Experts for Ensembles: A Systematic Empirical Study

Gangda Deng, Yuxin Yang, Ömer Faruk Akgül, and 4 more authors

arXiv preprint arXiv:2510.18370, 2025

arXiv Bib

@article{deng2025diverse,
  title = {Training Diverse Graph Experts for Ensembles: A Systematic Empirical Study},
  author = {Deng, Gangda and Yang, Yuxin and Akg{\"u}l, {\"O}mer Faruk and Zeng, Hanqing and Xia, Yinglong and Kannan, Rajgopal and Prasanna, Viktor},
  journal = {arXiv preprint arXiv:2510.18370},
  year = {2025},
}

LLM

Resa: Transparent Reasoning Models via SAEs

Shangshang Wang, Julian Asilis, Ömer Faruk Akgül, and 4 more authors

In NeurIPS 2025 Workshop on Efficient Reasoning, 2025

arXiv Bib

@inproceedings{wang2025resa,
  title = {Resa: Transparent Reasoning Models via SAEs},
  author = {Wang, Shangshang and Asilis, Julian and Akg{\"u}l, {\"O}mer Faruk and Bilgin, Enes Burak and Liu, Ollie and Fu, Deqing and Neiswanger, Willie},
  booktitle = {NeurIPS 2025 Workshop on Efficient Reasoning},
  year = {2025},
}

LLM

RECIPE-TKG: From Sparse History to Structured Reasoning for LLM-based Temporal Knowledge Graph Completion

Ömer Faruk Akgül, Feiyu Zhu, Yuxin Yang, and 2 more authors

In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2026

arXiv Bib

@inproceedings{akgul2026recipe,
  title = {RECIPE-TKG: From Sparse History to Structured Reasoning for LLM-based Temporal Knowledge Graph Completion},
  author = {Akg{\"u}l, {\"O}mer Faruk and Zhu, Feiyu and Yang, Yuxin and Kannan, Rajgopal and Prasanna, Viktor},
  booktitle = {Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL)},
  year = {2026},
}

LLM

Tina: Tiny Reasoning Models via LoRA

Shangshang Wang, Julian Asilis, Ömer Faruk Akgül, and 3 more authors

In The Thirteenth International Conference on Learning Representations (ICLR), 2026

arXiv Bib

@inproceedings{wang2026tina,
  title = {Tina: Tiny Reasoning Models via LoRA},
  author = {Wang, Shangshang and Asilis, Julian and Akg{\"u}l, {\"O}mer Faruk and Bilgin, Enes Burak and Liu, Ollie and Neiswanger, Willie},
  booktitle = {The Thirteenth International Conference on Learning Representations (ICLR)},
  year = {2026},
}

GNN

Conformal Prediction for Federated Graph Neural Networks with Missing Neighbor Information

Ömer Faruk Akgül, Rajgopal Kannan, and Viktor Prasanna

In Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2025

Bib

@inproceedings{akgul2025conformal,
  title = {Conformal Prediction for Federated Graph Neural Networks with Missing Neighbor Information},
  author = {Akg{\"u}l, {\"O}mer Faruk and Kannan, Rajgopal and Prasanna, Viktor},
  booktitle = {Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI)},
  year = {2025},
}

GNN

An Efficient Distributed Graph Engine for Deep Learning on Graphs

Gangda Deng, Ömer Faruk Akgül, Hongkuan Zhou, and 4 more authors

In Proceedings of the SC’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, 2023

Bib

@inproceedings{deng2023engine,
  title = {An Efficient Distributed Graph Engine for Deep Learning on Graphs},
  author = {Deng, Gangda and Akg{\"u}l, {\"O}mer Faruk and Zhou, Hongkuan and Zeng, Hanqing and Xia, Yinglong and Li, Jianbo and Prasanna, Viktor},
  booktitle = {Proceedings of the SC'23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis},
  pages = {922--931},
  year = {2023},
}