Ashwath Aithal

According to our database, Ashwath Aithal authored at least 15 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Heterogeneous Parallelism for Multimodal Large Language Model Training.

Yashaswi Karnati, Kamran Jafari, Akash Mehra, Li Ding, Pranav Prashant Thombre, Ali Roshan Ghias, Shifang Xu, Parth Mannan, Yu Yao, Hao Wu, Eric Harper, Ashwath Aithal, Nima Tajbakhsh

CoRR, May, 2026

X-Token: Projection-Guided Cross-Tokenizer Knowledge Distillation.

Sharath Turuvekere Sreenivas, Adithyakrishna Venkatesh Hanasoge, Mingyu Yang, Ali Taghibakhshi, Saurav Muralidharan, Ashwath Aithal, Pavlo Molchanov

CoRR, May, 2026

Star Elastic: Many-in-One Reasoning LLMs with Efficient Budget Control.

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

CoRR, May, 2026

Accelerating RL Post-Training Rollouts via System-Integrated Speculative Decoding.

Hayate Iso, Tiyasa Mitra, Sudipta Mondal, Rasoul Shafipour, Venmugil Elango, Terry Kong, Yuki Huang, Seonjin Na, Izzy Putterman, Benjamin Chislett, Maor Ashkenazi, Joseph Guman, Gerald Shen, Tugrul Konuk, Ashwath Aithal, Ritika Borkar, Ran Zilberstein, Bita Rouhani

CoRR, April, 2026

Scalable Training of Mixture-of-Experts Models with Megatron Core.

Zijie Yan, Hongxiao Bai, Xin Yao, Dennis Liu, Tong Liu, Hongbin Liu, Pingtian Li, Evan Wu, Shiqing Fan, Li Tao, Robin Zhang, Yuzhong Wang, Shifang Xu, Jack Chang, Xuwen Chen, Kunlun Li, Yan Bai, Gao Deng, Nan Zheng, Vijay Anand Korthikanti, Abhinav Khattar, Ethan He, Soham Govande, Sangkug Lym, Zhongbo Zhu, Qi Zhang, Haochen Yuan, Xiaowei Ren, Deyu Fu, Tailai Ma, Shunkang Zhang, Jiang Shao, Ray Wang, Vasudevan Rengasamy, Rachit Garg, Santosh Bhavani, Xipeng Li, Chandler Zhou, David Wu, Yingcan Wei, Ashwath Aithal, Michael Andersch, Mohammad Shoeybi, Jiajie Yao, June Yang

CoRR, March, 2026

2025

Nemotron Elastic: Towards Efficient Many-in-One Reasoning LLMs.

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

CoRR, November, 2025

MoE Parallel Folding: Heterogeneous Parallelism Mappings for Efficient Large-Scale MoE Model Training with Megatron Core.

Dennis Liu, Zijie Yan, Xin Yao, Tong Liu, Vijay Korthikanti, Evan Wu, Shiqing Fan, Gao Deng, Hongxiao Bai, Jianbin Chang, Ashwath Aithal, Michael Andersch, Mohammad Shoeybi, Jiajie Yao, Chandler Zhou, David Wu, Xipeng Li, June Yang

CoRR, April, 2025

Training Video Foundation Models with NVIDIA NeMo.

Zeeshan Patel, Ethan He, Parth Mannan, Xiaowei Ren, Ryan Wolf, Niket Agarwal, Jacob Samuel Huffman, Zhuoyao Wang, Carl Wang, Jack Chang, Yan Bai, Tommy Huang, Linnan Wang, Sahil Jain, Shanmugam Ramasamy, Joseph Jennings, Ekaterina Sirazitdinova, Oleg Sudakov, Mingyuan Ma, Bobby Chen, Forrest Lin, Hao Wang, Vasanth Rao Naik Sabavat, Sriharsha Niverty, Rong Ou, Pallab Bhattacharya, David Page, Nima Tajbakhsh, Ashwath Aithal

CoRR, March, 2025

Efficient Hybrid Language Model Compression through Group-Aware SSM Pruning.

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

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Llama 3 Meets MoE: Efficient Upcycling.

Aditya Vavre, Ethan He, Dennis Liu, Zijie Yan, June Yang, Nima Tajbakhsh, Ashwath Aithal

CoRR, 2024

Upcycling Large Language Models into Mixture of Experts.

Ethan He, Abhinav Khattar, Ryan Prenger, Vijay Korthikanti, Zijie Yan, Tong Liu, Shiqing Fan, Ashwath Aithal, Mohammad Shoeybi, Bryan Catanzaro

CoRR, 2024

NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment.

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

CoRR, 2024

Nemotron-4 15B Technical Report.

Jupinder Parmar, Shrimai Prabhumoye, Joseph Jennings, Mostofa Patwary, Sandeep Subramanian, Dan Su, Chen Zhu, Deepak Narayanan, Aastha Jhunjhunwala, Ayush Dattagupta, Vibhu Jawa, Jiwei Liu, Ameya Mahabaleshwarkar, Osvald Nitski, Annika Brundyn, James Maki, Miguel Martinez, Jiaxuan You, John Kamalu, Patrick LeGresley, Denys Fridman, Jared Casper, Ashwath Aithal, Oleksii Kuchaiev, Mohammad Shoeybi, Jonathan M. Cohen, Bryan Catanzaro

CoRR, 2024

2023

Hierarchical Graph Neural Network with Cross-Attention for Cross-Device User Matching.

Ali Taghibakhshi, Mingyuan Ma, Ashwath Aithal, Onur Yilmaz, Haggai Maron, Matthew West

Proceedings of the Big Data Analytics and Knowledge Discovery, 2023

2020

3D Object Detection on Point Clouds using Local Ground-aware and Adaptive Representation of scenes' surface.

Arun C. S. Kumar, Disha Ahuja, Ashwath Aithal

CoRR, 2020