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ORCIDAli Taghibakhshi
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2020 – today
- 2026
[i17]Ali Taghibakhshi, Ruisi Cai, Saurav Muralidharan, Sharath Turuvekere Sreenivas, Aditya Vavre, Ameya Sunil Mahabaleshwarkar, Bilal Kartal, Sheldon Liang, Marcin Chochowski, Zijia Chen, Akhiad Bercovich, Ran Zilberstein, Ran El-Yaniv, Yonatan Geifman, Daniel Korzekwa, Yoshi Suhara, Oluwatobi Olabiyi, Ashwath Aithal, Nima Tajbakhsh, Pavlo Molchanov:
Star Elastic: Many-in-One Reasoning LLMs with Efficient Budget Control. CoRR abs/2605.07182 (2026)- [i16]Sharath Turuvekere Sreenivas, Adithyakrishna Venkatesh Hanasoge, Mingyu Yang, Ali Taghibakhshi, Saurav Muralidharan, Ashwath Aithal, Pavlo Molchanov:
X-Token: Projection-Guided Cross-Tokenizer Knowledge Distillation. CoRR abs/2605.21699 (2026) - [i15]Akhiad Bercovich, Talor Abramovich, Daniel Afrimi, Shay Aharon, Nir Ailon, Vladimir Anisimov, Omer Ullman Argov, Maor Ashkenazi, Tomer Asida, Nave Assaf, Tomer Bar Natan, Alexander Bukharin, Grzegorz Chlebus, Marcin Chochowski, Eric Chung, Mohammad Dabbah, Carlo del Mundo, Ewa Dobrowolska, Ido Galil, Yaniv Galron, Amnon Geifman, Yonatan Geifman, Izik Golan, Alex Gronskiy, Tomasz Grzegorzek, Netanel Haber, Lior Kadoch, Grzegorz Karch, Tomer Keren, Abhinav Khattar, Amir Klein, Tugrul Konuk, Roi Koren, Daniel Korzekwa, Shaun Kotek, Konstantinos Krommydas, Itay Levy, Ofri Masad, Yoav Miron, Pavlo Molchanov, Shahar Mor, Zach Moshe, Saurav Muralidharan, Najeeb Nabwani, Besmira Nushi, Mostofa Patwary, Omri Puny, Johannes Rausch, Tomer Ronen, Sepehr Sameni, Itamar Schen, Elad Segal, Daniel Serebrenik, Ido Shahaf, Soumye Singhal, Daniil Sorokin, Sharath Turuvekere Sreenivas, Marta M. Stepniewska-Dziubinska, Ali Taghibakhshi, Nima Tajbakhsh, Oren Tropp, Dor Tzur, Anna Warno, Yi-Fu Wu, Michal Zawalski, Jiaqi Zeng, Yian Zhang, Ran Zilberstein, Amit Zuker, Ran El-Yaniv:
Nemotron-Labs-3-Puzzle-75B-A9B: Compressing Hybrid MoE LLMs. CoRR abs/2607.04371 (2026) - [i14]Mustafa Munir, Huy Vu, Shreyas Misra, Rohit Jena, Sajad Norouzi, Ali Taghibakhshi, Anis Ahmad, Anjul Patney, Pavlo Molchanov, Nima Tajbakhsh:
Accelerating Video Diffusion via Training-Free Trajectory Routing. CoRR abs/2609.30096 (2026) - 2025
- [j3]Nicolas Nytko
, Ali Taghibakhshi, Tareq Uz Zaman, Scott P. MacLachlan, Luke N. Olson, Matthew West:
Optimized Sparse Matrix Operations for Reverse Mode Automatic Differentiation. SIAM J. Sci. Comput. 47(5): 1115- (2025) - [c7]Ali Taghibakhshi, Sharath Turuvekere Sreenivas, Saurav Muralidharan, Marcin Chochowski, Yashaswi Karnati, Raviraj Joshi, Ameya Mahabaleshwarkar, Zijia Chen, Yoshi Suhara, Oluwatobi Olabiyi, Daniel Korzekwa, Mostofa Patwary, Mohammad Shoeybi, Jan Kautz, Bryan Catanzaro, Ashwath Aithal, Nima Tajbakhsh, Pavlo Molchanov:
Efficient Hybrid Language Model Compression through Group-Aware SSM Pruning. NeurIPS 2025 - [c6]Rohit Jena, Ali Taghibakhshi, Sahil Jain, Gerald Shen, Nima Tajbakhsh, Arash Vahdat:
Elucidating Optimal Reward-Diversity Tradeoffs in Text-to-Image Diffusion Models. WACV 2025: 232-242 - [i13]Jerome Ku, Eric Nguyen, David W. Romero, Garyk Brixi, Brandon Yang, Anton Vorontsov, Ali Taghibakhshi, Amy X. Lu, Dave P. Burke, Greg Brockman, Stefano Massaroli, Christopher Ré, Patrick D. Hsu, Brian L. Hie, Stefano Ermon, Michael Poli:
Systems and Algorithms for Convolutional Multi-Hybrid Language Models at Scale. CoRR abs/2503.01868 (2025) - [i12]Ali Taghibakhshi, Sharath Turuvekere Sreenivas, Saurav Muralidharan, Marcin Chochowski, Yashaswi Karnati, Raviraj Joshi, Ameya Sunil Mahabaleshwarkar, Zijia Chen, Yoshi Suhara, Oluwatobi Olabiyi, Daniel Korzekwa, Mostofa Patwary, Mohammad Shoeybi, Jan Kautz, Bryan Catanzaro, Ashwath Aithal, Nima Tajbakhsh, Pavlo Molchanov:
Efficient Hybrid Language Model Compression through Group-Aware SSM Pruning. CoRR abs/2504.11409 (2025) - [i11]Ali Taghibakhshi, Sharath Turuvekere Sreenivas, Saurav Muralidharan, Ruisi Cai, Marcin Chochowski, Ameya Sunil Mahabaleshwarkar, Yoshi Suhara, Oluwatobi Olabiyi, Daniel Korzekwa, Mostofa Patwary, Mohammad Shoeybi, Jan Kautz, Bryan Catanzaro, Ashwath Aithal, Nima Tajbakhsh, Pavlo Molchanov:
Nemotron Elastic: Towards Efficient Many-in-One Reasoning LLMs. CoRR abs/2511.16664 (2025) - 2024
- [j2]Tareq Uz Zaman, Nicolas Nytko, Ali Taghibakhshi, Scott P. MacLachlan, Luke N. Olson, Matthew West:
Generalizing reduction-based algebraic multigrid. Numer. Linear Algebra Appl. 31(3) (2024) - [j1]Tareq Uz Zaman, Nicolas Nytko, Ali Taghibakhshi, Scott P. MacLachlan, Luke N. Olson, Matthew West:
Generalizing Lloyd's Algorithm for Graph Clustering. SIAM J. Sci. Comput. 46(5): 2819- (2024) - [i10]Gerald Shen, Zhilin Wang, Olivier Delalleau, Jiaqi Zeng, Yi Dong, Daniel Egert, Shengyang Sun, Jimmy J. Zhang, Sahil Jain, Ali Taghibakhshi, Markel Sanz Ausin, Ashwath Aithal, Oleksii Kuchaiev:
NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment. CoRR abs/2405.01481 (2024) - [i9]Rohit Jena, Ali Taghibakhshi, Sahil Jain, Gerald Shen, Nima Tajbakhsh, Arash Vahdat:
Elucidating Optimal Reward-Diversity Tradeoffs in Text-to-Image Diffusion Models. CoRR abs/2409.06493 (2024) - 2023
- [c5]Ali Taghibakhshi, Mingyuan Ma, Ashwath Aithal, Onur Yilmaz, Haggai Maron, Matthew West:
Hierarchical Graph Neural Network with Cross-Attention for Cross-Device User Matching. DaWaK 2023: 303-315 - [c4]Ali Taghibakhshi, Nicolas Nytko, Tareq Uz Zaman, Scott P. MacLachlan, Luke N. Olson, Matthew West:
MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods. ICML 2023: 33381-33395 - [i8]Ali Taghibakhshi, Nicolas Nytko, Tareq-Uz-Zaman, Scott P. MacLachlan, Luke N. Olson, Matthew West:
MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods. CoRR abs/2301.11378 (2023) - [i7]Tareq Uz Zaman, Nicolas Nytko, Ali Taghibakhshi, Scott P. MacLachlan, Luke N. Olson, Matthew West:
Generalizing Lloyd's algorithm for graph clustering. CoRR abs/2303.01667 (2023) - [i6]Ali Taghibakhshi, Mingyuan Ma, Ashwath Aithal, Onur Yilmaz, Haggai Maron, Matthew West:
Hierarchical Graph Neural Network with Cross-Attention for Cross-Device User Matching. CoRR abs/2304.03215 (2023) - 2022
- [c3]Ali Taghibakhshi, Nicolas Nytko, Tareq Uz Zaman, Scott P. MacLachlan, Luke N. Olson, Matthew West:
Learning Interface Conditions in Domain Decomposition Solvers. NeurIPS 2022 - [i5]Ali Taghibakhshi, Nicolas Nytko, Tareq Uz Zaman, Scott P. MacLachlan, Luke N. Olson, Matthew West:
Learning Interface Conditions in Domain Decomposition Solvers. CoRR abs/2205.09833 (2022) - [i4]Nicolas Nytko, Ali Taghibakhshi, Tareq-Uz-Zaman, Scott P. MacLachlan, Luke N. Olson, Matt West:
Optimized Sparse Matrix Operations for Reverse Mode Automatic Differentiation. CoRR abs/2212.05159 (2022) - [i3]Tareq Uz Zaman, Nicolas Nytko, Ali Taghibakhshi, Scott P. MacLachlan, Luke N. Olson, Matthew West:
Generalizing Reduction-Based Algebraic Multigrid. CoRR abs/2212.08371 (2022) - 2021
- [c2]Ali Taghibakhshi, Nathan Ogden, Matthew West:
Local Navigation and Docking of an Autonomous Robot Mower Using Reinforcement Learning and Computer Vision. ICCAE 2021: 10-14 - [c1]Ali Taghibakhshi, Scott P. MacLachlan, Luke N. Olson, Matthew West:
Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning. NeurIPS 2021: 12129-12140 - [i2]Ali Taghibakhshi, Nathan Ogden, Matthew West:
Local Navigation and Docking of an Autonomous Robot Mower using Reinforcement Learning and Computer Vision. CoRR abs/2101.06248 (2021) - [i1]Ali Taghibakhshi, Scott P. MacLachlan, Luke N. Olson, Matthew West:
Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning. CoRR abs/2106.01854 (2021)
Coauthor Index
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