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ORCIDRaghuraman Krishnamoorthi
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2020 – today
- 2024
[c13]Lemeng Wu, Dilin Wang, Meng Li, Yunyang Xiong, Raghuraman Krishnamoorthi, Qiang Liu, Vikas Chandra:
PathFusion: Path-Consistent Lidar-Camera Deep Feature Fusion. 3DV 2024: 313-323- [c12]Zechun Liu, Barlas Oguz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, Yangyang Shi, Raghuraman Krishnamoorthi, Vikas Chandra:
LLM-QAT: Data-Free Quantization Aware Training for Large Language Models. ACL (Findings) 2024: 467-484 - [c11]Ganesh Jawahar, Haichuan Yang, Yunyang Xiong, Zechun Liu, Dilin Wang, Fei Sun, Meng Li, Aasish Pappu, Barlas Oguz, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Raghuraman Krishnamoorthi, Vikas Chandra:
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts. ACL (Findings) 2024: 10424-10443 - [c10]Yunyang Xiong, Bala Varadarajan, Lemeng Wu, Xiaoyu Xiang, Fanyi Xiao, Chenchen Zhu, Xiaoliang Dai, Dilin Wang, Fei Sun, Forrest N. Iandola, Raghuraman Krishnamoorthi, Vikas Chandra:
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything. CVPR 2024: 16111-16121 - [c9]Yuan Shangguan, Haichuan Yang, Danni Li, Chunyang Wu, Yassir Fathullah, Dilin Wang, Ayushi Dalmia, Raghuraman Krishnamoorthi, Ozlem Kalinli, Junteng Jia, Jay Mahadeokar, Xin Lei, Mike Seltzer, Vikas Chandra:
TODM: Train Once Deploy Many Efficient Supernet-Based RNN-T Compression For On-Device ASR Models. ICASSP 2024: 10216-10220 - [c8]Zhangheng Li, Shiwei Liu, Tianlong Chen, Ajay Kumar Jaiswal, Zhenyu Zhang, Dilin Wang, Raghuraman Krishnamoorthi, Shiyu Chang, Zhangyang Wang:
Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once. ICML 2024 - [c7]Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra:
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases. ICML 2024 - [i23]Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra:
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases. CoRR abs/2402.14905 (2024) - [i22]Bo Liu, Lemeng Wu, Lizhang Chen, Kaizhao Liang, Jiaxu Zhu, Chen Liang, Raghuraman Krishnamoorthi, Qiang Liu:
Communication Efficient Distributed Training with Distributed Lion. CoRR abs/2404.00438 (2024) - [i21]Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort:
SpinQuant: LLM quantization with learned rotations. CoRR abs/2405.16406 (2024) - [i20]Mingchen Zhuge, Changsheng Zhao, Dylan R. Ashley, Wenyi Wang, Dmitrii Khizbullin, Yunyang Xiong, Zechun Liu, Ernie Chang, Raghuraman Krishnamoorthi, Yuandong Tian, Yangyang Shi, Vikas Chandra, Jürgen Schmidhuber:
Agent-as-a-Judge: Evaluate Agents with Agents. CoRR abs/2410.10934 (2024) - 2023
- [c6]Zechun Liu, Barlas Oguz, Aasish Pappu, Yangyang Shi, Raghuraman Krishnamoorthi:
Binary and Ternary Natural Language Generation. ACL (1) 2023: 65-77 - [c5]Lemeng Wu, Dilin Wang, Chengyue Gong, Xingchao Liu, Yunyang Xiong, Rakesh Ranjan, Raghuraman Krishnamoorthi, Vikas Chandra, Qiang Liu:
Fast Point Cloud Generation with Straight Flows. CVPR 2023: 9445-9454 - [i19]Zechun Liu, Barlas Oguz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, Yangyang Shi, Raghuraman Krishnamoorthi, Vikas Chandra:
LLM-QAT: Data-Free Quantization Aware Training for Large Language Models. CoRR abs/2305.17888 (2023) - [i18]Zechun Liu, Barlas Oguz, Aasish Pappu, Yangyang Shi, Raghuraman Krishnamoorthi:
Binary and Ternary Natural Language Generation. CoRR abs/2306.01841 (2023) - [i17]Ganesh Jawahar, Haichuan Yang, Yunyang Xiong, Zechun Liu, Dilin Wang, Fei Sun, Meng Li, Aasish Pappu, Barlas Oguz, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Raghuraman Krishnamoorthi, Vikas Chandra:
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts. CoRR abs/2306.04845 (2023) - [i16]Yuan Shangguan, Haichuan Yang, Danni Li, Chunyang Wu, Yassir Fathullah, Dilin Wang, Ayushi Dalmia, Raghuraman Krishnamoorthi, Ozlem Kalinli, Junteng Jia, Jay Mahadeokar, Xin Lei, Mike Seltzer, Vikas Chandra:
TODM: Train Once Deploy Many Efficient Supernet-Based RNN-T Compression For On-device ASR Models. CoRR abs/2309.01947 (2023) - [i15]Jun Chen, Deyao Zhu, Xiaoqian Shen, Xiang Li, Zechun Liu, Pengchuan Zhang, Raghuraman Krishnamoorthi, Vikas Chandra, Yunyang Xiong, Mohamed Elhoseiny:
MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning. CoRR abs/2310.09478 (2023) - [i14]Yunyang Xiong, Bala Varadarajan, Lemeng Wu, Xiaoyu Xiang, Fanyi Xiao, Chenchen Zhu, Xiaoliang Dai, Dilin Wang, Fei Sun, Forrest N. Iandola, Raghuraman Krishnamoorthi, Vikas Chandra:
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything. CoRR abs/2312.00863 (2023) - [i13]Zhuoran Yu, Chenchen Zhu, Sean Chang Culatana, Raghuraman Krishnamoorthi, Fanyi Xiao, Yong Jae Lee:
Diversify, Don't Fine-Tune: Scaling Up Visual Recognition Training with Synthetic Images. CoRR abs/2312.02253 (2023) - [i12]Saksham Suri, Fanyi Xiao, Animesh Sinha, Sean Chang Culatana, Raghuraman Krishnamoorthi, Chenchen Zhu, Abhinav Shrivastava:
Gen2Det: Generate to Detect. CoRR abs/2312.04566 (2023) - [i11]Balakrishnan Varadarajan, Bilge Soran, Forrest N. Iandola, Xiaoyu Xiang, Yunyang Xiong, Lemeng Wu, Chenchen Zhu, Raghuraman Krishnamoorthi, Vikas Chandra:
SqueezeSAM: User friendly mobile interactive segmentation. CoRR abs/2312.06736 (2023) - 2022
- [c4]Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Cheng Wan, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin:
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks. ICML 2022: 6849-6862 - [c3]Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad:
BiT: Robustly Binarized Multi-distilled Transformer. NeurIPS 2022 - [c2]Assaf Eisenman, Kiran Kumar Matam, Steven Ingram, Dheevatsa Mudigere, Raghuraman Krishnamoorthi, Krishnakumar Nair, Misha Smelyanskiy, Murali Annavaram:
Check-N-Run: a Checkpointing System for Training Deep Learning Recommendation Models. NSDI 2022: 929-943 - [c1]Chunxi Liu, Yuan Shangguan, Haichuan Yang, Yangyang Shi, Raghuraman Krishnamoorthi, Ozlem Kalinli:
Learning a Dual-Mode Speech Recognition Model VIA Self-Pruning. SLT 2022: 273-279 - [i10]Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad:
BiT: Robustly Binarized Multi-distilled Transformer. CoRR abs/2205.13016 (2022) - [i9]Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Cheng Wan, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin:
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks. CoRR abs/2206.00843 (2022) - [i8]Chunxi Liu, Yuan Shangguan, Haichuan Yang, Yangyang Shi, Raghuraman Krishnamoorthi, Ozlem Kalinli:
Learning a Dual-Mode Speech Recognition Model via Self-Pruning. CoRR abs/2207.11906 (2022) - [i7]Haichuan Yang, Zhaojun Yang, Li Wan, Biqiao Zhang, Yangyang Shi, Yiteng Huang, Ivaylo Enchev, Limin Tang, Raziel Alvarez, Ming Sun, Xin Lei, Raghuraman Krishnamoorthi, Vikas Chandra:
LiCo-Net: Linearized Convolution Network for Hardware-efficient Keyword Spotting. CoRR abs/2211.04635 (2022) - [i6]Lemeng Wu, Dilin Wang, Chengyue Gong, Xingchao Liu, Yunyang Xiong, Rakesh Ranjan, Raghuraman Krishnamoorthi, Vikas Chandra, Qiang Liu:
Fast Point Cloud Generation with Straight Flows. CoRR abs/2212.01747 (2022) - [i5]Lemeng Wu, Dilin Wang, Meng Li, Yunyang Xiong, Raghuraman Krishnamoorthi, Qiang Liu, Vikas Chandra:
PathFusion: Path-consistent Lidar-Camera Deep Feature Fusion. CoRR abs/2212.06244 (2022) - 2021
- [j2]Zhaoxia Deng
, Jongsoo Park, Ping Tak Peter Tang, Haixin Liu, Jie Yang, Hector Yuen, Jianyu Huang, Daya Shanker Khudia, Xiaohan Wei, Ellie Wen, Dhruv Choudhary, Raghuraman Krishnamoorthi, Carole-Jean Wu, Nadathur Satish, Changkyu Kim, Maxim Naumov, Sam Naghshineh, Mikhail Smelyanskiy:
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. IEEE Micro 41(5): 93-100 (2021) - [i4]Zhaoxia Deng, Jongsoo Park, Ping Tak Peter Tang, Haixin Liu, Jie Yang, Hector Yuen, Jianyu Huang, Daya Shanker Khudia, Xiaohan Wei, Ellie Wen, Dhruv Choudhary, Raghuraman Krishnamoorthi, Carole-Jean Wu, Nadathur Satish, Changkyu Kim, Maxim Naumov, Sam Naghshineh, Mikhail Smelyanskiy:
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. CoRR abs/2105.12676 (2021) - 2020
- [i3]Assaf Eisenman, Kiran Kumar Matam, Steven Ingram, Dheevatsa Mudigere, Raghuraman Krishnamoorthi, Murali Annavaram, Krishnakumar Nair, Misha Smelyanskiy:
Check-N-Run: A Checkpointing System for Training Recommendation Models. CoRR abs/2010.08679 (2020)
2010 – 2019
- 2019
- [i2]Maxim Naumov, Dheevatsa Mudigere, Hao-Jun Michael Shi, Jianyu Huang, Narayanan Sundaraman, Jongsoo Park, Xiaodong Wang, Udit Gupta, Carole-Jean Wu, Alisson G. Azzolini, Dmytro Dzhulgakov, Andrey Mallevich, Ilia Cherniavskii, Yinghai Lu, Raghuraman Krishnamoorthi, Ansha Yu, Volodymyr Kondratenko, Stephanie Pereira, Xianjie Chen, Wenlin Chen, Vijay Rao, Bill Jia, Liang Xiong, Misha Smelyanskiy:
Deep Learning Recommendation Model for Personalization and Recommendation Systems. CoRR abs/1906.00091 (2019) - 2018
- [i1]Raghuraman Krishnamoorthi:
Quantizing deep convolutional networks for efficient inference: A whitepaper. CoRR abs/1806.08342 (2018)
2000 – 2009
- 2007
- [j1]Murali R. Chari, Fuyun Ling, Ashok Mantravadi, Raghuraman Krishnamoorthi, Rajiv Vijayan, G. Kent Walker, Rob Chandhok:
FLO Physical Layer: An Overview. IEEE Trans. Broadcast. 53(1): 145-160 (2007)
Coauthor Index
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