Naigang Wang - RankMe

52 papers A* 9A 4C 1Misc 2Journal 29Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Frayed RoPE and Long Inputs: A Geometric Perspective. CoRR Davis Wertheimer, Aozhong Zhang, Derrick Liu, Penghang Yin, Naigang Wang
2026	J	`jnl`	Is Finer Better? The Limits of Microscaling Formats in Large Language Models. CoRR Andrea Fasoli, Monodeep Kar, Chi-Chun (Charlie) Liu, Swagath Venkataramani, Viji Srinivasan, Leland Chang, Naigang Wang
2026	J	`jnl`	LoDAdaC: a unified local training-based decentralized framework with adaptive gradients and compressed communication. Trans. Mach. Learn. Res. Wei Liu, Anweshit Panda, Ujwal Pandey, Haven Cook, George M. Slota, Naigang Wang, Jie Chen, Yangyang Xu
2025	J	`jnl`	Accelerating LLM Inference via Dynamic KV Cache Placement in Heterogeneous Memory System. IEEE Comput. Archit. Lett. Yunhua Fang, Rui Xie, Asad Ul Haq, Linsen Ma, Kaoutar El Maghraoui, Naigang Wang, Meng Wang, Liu Liu, Tong Zhang
2025	J	`jnl`	Accelerating LLM Inference via Dynamic KV Cache Placement in Heterogeneous Memory System. CoRR Yunhua Fang, Rui Xie, Asad Ul Haq, Linsen Ma, Kaoutar El Maghraoui, Naigang Wang, Meng Wang, Liu Liu, Tong Zhang
2025	J	`jnl`	CLoQ: Enhancing Fine-Tuning of Quantized LLMs via Calibrated LoRA Initialization. CoRR Yanxia Deng, Aozhong Zhang, Naigang Wang, Selcuk Gurses, Zi Yang, Penghang Yin
2025	J	`jnl`	CLoQ: Enhancing Fine-Tuning of Quantized LLMs via Calibrated LoRA Initialization. Trans. Mach. Learn. Res. Yanxia Deng, Aozhong Zhang, Selcuk Gurses, Naigang Wang, Zi Yang, Penghang Yin
2025	J	`jnl`	COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization. IEEE Access Aozhong Zhang, Zi Yang, Naigang Wang, Yingyong Qi, Jack Xin, Xin Li, Penghang Yin
2025	J	`jnl`	Compressed Decentralized Momentum Stochastic Gradient Methods for Nonconvex Optimization. CoRR Wei Liu, Anweshit Panda, Ujwal Pandey, Christopher Brissette, Yikang Shen, George M. Slota, Naigang Wang, Jie Chen, Yangyang Xu
2025	J	`jnl`	Compressed Decentralized Momentum Stochastic Gradient Methods for Nonconvex Optimization. Trans. Mach. Learn. Res. Wei Liu, Anweshit Panda, Ujwal Pandey, Christopher Brissette, Yikang Shen, George M. Slota, Naigang Wang, Jie Chen, Yangyang Xu
2025	J	`jnl`	DiaBlo: Diagonal Blocks Are Sufficient For Finetuning. CoRR Selcuk Gurses, Aozhong Zhang, Yanxia Deng, Xun Dong, Xin Li, Naigang Wang, Penghang Yin, Zi Yang
2025	J	`jnl`	EvidenceMoE: A Physics-Guided Mixture-of-Experts with Evidential Critics for Advancing Fluorescence Light Detection and Ranging in Scattering Media. CoRR Ismail Erbas, Ferhat Demirkiran, Karthik Swaminathan, Naigang Wang, Navid Ibtehaj Nizam, Stefan T. Radev, Kaoutar El Maghraoui, Xavier Intes, Vikas Pandey
2025	J	`jnl`	Generative AI Through CAS Lens: An Integrated Overview of Algorithmic Optimizations, Architectural Advances, and Automated Designs. IEEE J. Emerg. Sel. Topics Circuits Syst. Chuan Zhang, You You, Naigang Wang, Jongsun Park, Li Zhang
2025	J	`jnl`	Guest Editorial Generative Artificial Intelligence Compute: Algorithms, Implementations, and Applications to CAS. IEEE J. Emerg. Sel. Topics Circuits Syst. Chuan Zhang, Naigang Wang, Jongsun Park, Li Zhang
2025	A	`conf`	No Time to Lose: Enabling Real-Time Fluorescence Lifetime Imaging on Resource-constrained FPGAs Through Efficient Scheduling. FPGA Ismail Erbas, Aporva Amarnath, Vikas Pandey, Karthik Swaminathan, Naigang Wang, Xavier Intes
2025	Misc	`conf`	Onboard Decisions and Cloud-Scale LLM Planning: Split Reasoning and Collaborative Intelligence for Autonomous Driving. SEC Meng Ma, Shuyang Li, Kaicong Huang, Talha Azfar, Naigang Wang, Ruimin Ke
2024	A*	`conf`	A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts. ICML Mohammed Nowaz Rabbani Chowdhury, Meng Wang, Kaoutar El Maghraoui, Naigang Wang, Pin-Yu Chen, Christopher D. Carothers
2024	J	`jnl`	A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts. CoRR Mohammed Nowaz Rabbani Chowdhury, Meng Wang, Kaoutar El Maghraoui, Naigang Wang, Pin-Yu Chen, Christopher D. Carothers
2024	J	`jnl`	COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization. CoRR Aozhong Zhang, Zi Yang, Naigang Wang, Yingyong Qin, Jack Xin, Xin Li, Penghang Yin
2024	J	`jnl`	Compressing Recurrent Neural Networks for FPGA-accelerated Implementation in Fluorescence Lifetime Imaging. CoRR Ismail Erbas, Vikas Pandey, Aporva Amarnath, Naigang Wang, Karthik Swaminathan, Stefan T. Radev, Xavier Intes
2024	A	`conf`	Improved Techniques for Quantizing Deep Networks with Adaptive Bit-Widths. WACV Ximeng Sun, Rameswar Panda, Chun-Fu Richard Chen, Naigang Wang, Bowen Pan, Aude Oliva, Rogério Feris, Kate Saenko
2024	A*	`conf`	MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization. NeurIPS Aozhong Zhang, Naigang Wang, Yanxia Deng, Xin Li, Zi Yang, Penghang Yin
2024	J	`jnl`	MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization. CoRR Aozhong Zhang, Naigang Wang, Yanxia Deng, Xin Li, Zi Yang, Penghang Yin
2024	J	`jnl`	Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization. CoRR Aniruddha Nrusimha, Mayank Mishra, Naigang Wang, Dan Alistarh, Rameswar Panda, Yoon Kim
2024	J	`jnl`	Unlocking Real-Time Fluorescence Lifetime Imaging: Multi-Pixel Parallelism for FPGA-Accelerated Processing. CoRR Ismail Erbas, Aporva Amarnath, Vikas Pandey, Karthik Swaminathan, Naigang Wang, Xavier Intes
2022	J	`jnl`	A 7-nm Four-Core Mixed-Precision AI Chip With 26.2-TFLOPS Hybrid-FP8 Training, 104.9-TOPS INT4 Inference, and Workload-Aware Throttling. IEEE J. Solid State Circuits Sae Kyu Lee, Ankur Agrawal, Joel Silberman, Matthew M. Ziegler, Mingu Kang, Swagath Venkataramani, Nianzheng Cao, Bruce M. Fleischer, Michael Guillorn, Matthew Cohen, Silvia M. Mueller, Jinwook Oh, Martin Lutz, Jinwook Jung, Siyu Koswatta, Ching Zhou, Vidhi Zalani, Monodeep Kar, James Bonanno, Robert Casatuta, Chia-Yu Chen, Jungwook Choi, Howard Haynie, Alyssa Herbert, Radhika Jain, Kyu-Hyoun Kim, Yulong Li, Zhibin Ren, Scot Rider, Marcel Schaal, Kerstin Schelm, Michael Scheuermann, Xiao Sun, Hung Tran, Naigang Wang, Wei Wang, Xin Zhang, Vinay Shah, Brian W. Curran, Vijayalakshmi Srinivasan, Pong-Fei Lu, Sunil Shukla, Kailash Gopalakrishnan, Leland Chang
2022	A*	`conf`	Deep Compression of Pre-trained Transformer Models. NeurIPS Naigang Wang, Chi-Chun (Charlie) Liu, Swagath Venkataramani, Sanchari Sen, Chia-Yu Chen, Kaoutar El Maghraoui, Vijayalakshmi Srinivasan, Leland Chang
2021	A	`conf`	4-Bit Quantization of LSTM-Based Speech Recognition Models. Interspeech Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Xiao Sun, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei Zhang, Zoltán Tüske, Kailash Gopalakrishnan
2021	J	`jnl`	4-bit Quantization of LSTM-based Speech Recognition Models. CoRR Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Xiao Sun, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei Zhang, Zoltán Tüske, Kailash Gopalakrishnan
2021	—	`conf`	A 7nm 4-Core AI Chip with 25.6TFLOPS Hybrid FP8 Training, 102.4TOPS INT4 Inference and Workload-Aware Throttling. ISSCC Ankur Agrawal, Sae Kyu Lee, Joel Silberman, Matthew M. Ziegler, Mingu Kang, Swagath Venkataramani, Nianzheng Cao, Bruce M. Fleischer, Michael Guillorn, Matt Cohen, Silvia M. Mueller, Jinwook Oh, Martin Lutz, Jinwook Jung, Siyu Koswatta, Ching Zhou, Vidhi Zalani, James Bonanno, Robert Casatuta, Chia-Yu Chen, Jungwook Choi, Howard Haynie, Alyssa Herbert, Radhika Jain, Monodeep Kar, Kyu-Hyoun Kim, Yulong Li, Zhibin Ren, Scot Rider, Marcel Schaal, Kerstin Schelm, Michael Scheuermann, Xiao Sun, Hung Tran, Naigang Wang, Wei Wang, Xin Zhang, Vinay Shah, Brian W. Curran, Vijayalakshmi Srinivasan, Pong-Fei Lu, Sunil Shukla, Leland Chang, Kailash Gopalakrishnan
2021	J	`jnl`	A Comprehensive Survey on Hardware-Aware Neural Architecture Search. CoRR Hadjer Benmeziane, Kaoutar El Maghraoui, Hamza Ouarnoughi, Smaïl Niar, Martin Wistuba, Naigang Wang
2021	J	`jnl`	All at Once Network Quantization via Collaborative Knowledge Transfer. CoRR Ximeng Sun, Rameswar Panda, Chun-Fu Chen, Naigang Wang, Bowen Pan, Kailash Gopalakrishnan, Aude Oliva, Rogério Feris, Kate Saenko
2021	A*	`conf`	Hardware-Aware Neural Architecture Search: Survey and Taxonomy. IJCAI Hadjer Benmeziane, Kaoutar El Maghraoui, Hamza Ouarnoughi, Smaïl Niar, Martin Wistuba, Naigang Wang
2021	A*	`conf`	RaPiD: AI Accelerator for Ultra-low Precision Training and Inference. ISCA Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Wang, Sanchari Sen, Jintao Zhang, Ankur Agrawal, Monodeep Kar, Shubham Jain, Alberto Mannari, Hoang Tran, Yulong Li, Eri Ogawa, Kazuaki Ishizaki, Hiroshi Inoue, Marcel Schaal, Mauricio J. Serrano, Jungwook Choi, Xiao Sun, Naigang Wang, Chia-Yu Chen, Allison Allain, James Bonanno, Nianzheng Cao, Robert Casatuta, Matthew Cohen, Bruce M. Fleischer, Michael Guillorn, Howard Haynie, Jinwook Jung, Mingu Kang, Kyu-Hyoun Kim, Siyu Koswatta, Sae Kyu Lee, Martin Lutz, Silvia M. Mueller, Jinwook Oh, Ashish Ranjan, Zhibin Ren, Scot Rider, Kerstin Schelm, Michael Scheuermann, Joel Silberman, Jie Yang, Vidhi Zalani, Xin Zhang, Ching Zhou, Matthew M. Ziegler, Vinay Shah, Moriyoshi Ohara, Pong-Fei Lu, Brian W. Curran, Sunil Shukla, Leland Chang, Kailash Gopalakrishnan
2021	J	`jnl`	ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training. CoRR Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan
2020	—	`conf`	A 3.0 TFLOPS 0.62V Scalable Processor Core for High Compute Utilization AI Training and Inference. VLSI Circuits Jinwook Oh, Sae Kyu Lee, Mingu Kang, Matthew M. Ziegler, Joel Silberman, Ankur Agrawal, Swagath Venkataramani, Bruce M. Fleischer, Michael Guillorn, Jungwook Choi, Wei Wang, Silvia M. Mueller, Shimon Ben-Yehuda, James Bonanno, Nianzheng Cao, Robert Casatuta, Chia-Yu Chen, Matt Cohen, Ophir Erez, Thomas W. Fox, George Gristede, Howard Haynie, Vicktoria Ivanov, Siyu Koswatta, Shih-Hsien Lo, Martin Lutz, Gary W. Maier, Alex Mesh, Yevgeny Nustov, Scot Rider, Marcel Schaal, Michael Scheuermann, Xiao Sun, Naigang Wang, Fanchieh Yee, Ching Zhou, Vinay Shah, Brian W. Curran, Vijayalakshmi Srinivasan, Pong-Fei Lu, Sunil Shukla, Kailash Gopalakrishnan, Leland Chang
2020	J	`jnl`	Efficient AI System Design With Cross-Layer Approximate Computing. Proc. IEEE Swagath Venkataramani, Xiao Sun, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Mingu Kang, Ankur Agarwal, Jinwook Oh, Shubham Jain, Tina Babinsky, Nianzheng Cao, Thomas W. Fox, Bruce M. Fleischer, George Gristede, Michael Guillorn, Howard Haynie, Hiroshi Inoue, Kazuaki Ishizaki, Michael J. Klaiber, Shih-Hsien Lo, Gary W. Maier, Silvia M. Mueller, Michael Scheuermann, Eri Ogawa, Marcel Schaal, Mauricio J. Serrano, Joel Silberman, Christos Vezyrtzis, Wei Wang, Fanchieh Yee, Jintao Zhang, Matthew M. Ziegler, Ching Zhou, Moriyoshi Ohara, Pong-Fei Lu, Brian W. Curran, Sunil Shukla, Vijayalakshmi Srinivasan, Leland Chang, Kailash Gopalakrishnan
2020	A*	`conf`	ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training. NeurIPS Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan
2020	A*	`conf`	Ultra-Low Precision 4-bit Training of Deep Neural Networks. NeurIPS Xiao Sun, Naigang Wang, Chia-Yu Chen, Jiamin Ni, Ankur Agrawal, Xiaodong Cui, Swagath Venkataramani, Kaoutar El Maghraoui, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan
2019	—	`conf`	Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. ICLR (Poster) Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan
2019	J	`jnl`	Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. CoRR Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan
2019	C	`conf`	DLFloat: A 16-b Floating Point Format Designed for Deep Learning Training and Inference. ARITH Ankur Agrawal, Bruce M. Fleischer, Silvia M. Mueller, Xiao Sun, Naigang Wang, Jungwook Choi, Kailash Gopalakrishnan
2019	A*	`conf`	Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks. NeurIPS Xiao Sun, Jungwook Choi, Chia-Yu Chen, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Xiaodong Cui, Wei Zhang, Kailash Gopalakrishnan
2019	Misc	`conf`	Innovate Practices on CyberSecurity of Hardware Semiconductor Devices. VTS Alfred L. Crouch, Peter L. Levin, Jennifer Dworak, Lakshmi Ramakrishnan, Yuhe Xia, Chi Zhang, Daniel Engels, Gary Evans, Ping Gui, Scott McWilliams, Saurabh Gupta, Franco Stellari, Naigang Wang, Peilin Song
2018	—	`conf`	A Scalable Multi- TeraOPS Deep Learning Processor Core for AI Trainina and Inference. VLSI Circuits Bruce M. Fleischer, Sunil Shukla, Matthew M. Ziegler, Joel Silberman, Jinwook Oh, Vijayalakshmi Srinivasan, Jungwook Choi, Silvia M. Mueller, Ankur Agrawal, Tina Babinsky, Nianzheng Cao, Chia-Yu Chen, Pierce Chuang, Thomas W. Fox, George Gristede, Michael Guillorn, Howard Haynie, Michael J. Klaiber, Dongsoo Lee, Shih-Hsien Lo, Gary W. Maier, Michael Scheuermann, Swagath Venkataramani, Christos Vezyrtzis, Naigang Wang, Fanchieh Yee, Ching Zhou, Pong-Fei Lu, Brian W. Curran, Leland Chang, Kailash Gopalakrishnan
2018	A	`conf`	Across the Stack Opportunities for Deep Learning Acceleration. ISLPED Vijayalakshmi Srinivasan, Bruce M. Fleischer, Sunil Shukla, Matthew M. Ziegler, Joel Silberman, Jinwook Oh, Jungwook Choi, Silvia M. Mueller, Ankur Agrawal, Tina Babinsky, Nianzheng Cao, Chia-Yu Chen, Pierce Chuang, Thomas W. Fox, George Gristede, Michael Guillorn, Howard Haynie, Michael J. Klaiber, Dongsoo Lee, Shih-Hsien Lo, Gary W. Maier, Michael Scheuermann, Swagath Venkataramani, Christos Vezyrtzis, Naigang Wang, Fanchieh Yee, Ching Zhou, Pong-Fei Lu, Brian W. Curran, Leland Chang, Kailash Gopalakrishnan
2018	—	`conf`	Novel IC Sub-Threshold IDDQ Signature And Its Relationship To Aging During High Voltage Stress. ESSDERC Franco Stellari, Naigang Wang, Peilin Song
2018	A*	`conf`	Training Deep Neural Networks with 8-bit Floating Point Numbers. NeurIPS Naigang Wang, Jungwook Choi, Daniel Brand, Chia-Yu Chen, Kailash Gopalakrishnan
2018	J	`jnl`	Training Deep Neural Networks with 8-bit Floating Point Numbers. CoRR Naigang Wang, Jungwook Choi, Daniel Brand, Chia-Yu Chen, Kailash Gopalakrishnan
2015	—	`conf`	An 82%-efficient multiphase voltage-regulator 3D interposer with on-chip magnetic inductors. VLSIC Kevin Tien, Noah Sturcken, Naigang Wang, Jae-Woong Nah, Bing Dang, Eugene J. O'Sullivan, Paul S. Andry, Michele Petracca, Luca P. Carloni, William J. Gallagher, Kenneth L. Shepard
2013	J	`jnl`	A 2.5D Integrated Voltage Regulator Using Coupled-Magnetic-Core Inductors on Silicon Interposer. IEEE J. Solid State Circuits Noah Sturcken, Eugene J. O'Sullivan, Naigang Wang, Philipp Herget, Bucknell C. Webb, Lubomyr T. Romankiw, Michele Petracca, Ryan Davies, Robert E. Fontana Jr., Gary M. Decad, Ioannis Kymissis, Angel V. Peterchev, Luca P. Carloni, William J. Gallagher, Kenneth L. Shepard
2012	—	`conf`	A 2.5D integrated voltage regulator using coupled-magnetic-core inductors on silicon interposer delivering 10.8A/mm ISSCC Noah Sturcken, Eugene J. O'Sullivan, Naigang Wang, Philipp Herget, Bucknell C. Webb, Lubomyr T. Romankiw, Michele Petracca, Ryan Davies, Robert E. Fontana Jr., Gary M. Decad, Ioannis Kymissis, Angel V. Peterchev, Luca P. Carloni, William J. Gallagher, Kenneth L. Shepard