Minjia Zhang - RankMe

140 papers A* 28A 9B 9C 1Misc 3Journal 73Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FedMT: Multitask Federated Learning With Competitive GPU Resource Sharing. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Yongbo Yu, Fuxun Yu, Zirui Xu, Di Wang, Minjia Zhang, Ang Li, Chenchen Liu, Zhi Tian, Xiang Chen
2026	J	`jnl`	Gated Differential Linear Attention: A Linear-Time Decoder for High-Fidelity Medical Segmentation. CoRR Hongbo Zheng, Afshin Bozorgpour, Dorit Merhof, Minjia Zhang
2026	J	`jnl`	Hidden States as Early Signals: Step-level Trace Evaluation and Pruning for Efficient Test-Time Scaling. CoRR Zhixiang Liang, Beichen Huang, Zheng Wang, Minjia Zhang
2026	J	`jnl`	SuperInfer: SLO-Aware Rotary Scheduling and Memory Management for LLM Inference on Superchips. CoRR Jiahuan Yu, Mingtao Hu, Zichao Lin, Minjia Zhang
2026	—	`conf`	SuperOffload: Unleashing the Power of Large-Scale LLM Training on Superchips. ASPLOS (1) Xinyu Lian, Masahiro Tanaka, Olatunji Ruwase, Minjia Zhang
2026	A*	`conf`	Teaching Large Language Models to Maintain Contextual Faithfulness via Synthetic Tasks and Reinforcement Learning. AAAI Shuzheng Si, Haozhe Zhao, Cheng Gao, Yuzhuo Bai, Zhitong Wang, Bofei Gao, Kangyang Luo, Wenhao Li, Yufei Huang, Gang Chen, Fanchao Qi, Minjia Zhang, Baobao Chang, Maosong Sun
2026	J	`jnl`	Trustworthy Agent Network: Trust in Agent Networks Must Be Baked In, Not Bolted On. IACR Cryptol. ePrint Arch. Yixiang Yao, Yuhang Yao, Xinyi Fan, Jiechao Gao, Jie Wang, Minjia Zhang, Srivatsan Ravi, Carlee Joe-Wong
2025	J	`jnl`	A Goal Without a Plan Is Just a Wish: Efficient and Effective Global Planner Training for Long-Horizon Agent Tasks. CoRR Shuzheng Si, Haozhe Zhao, Kangyang Luo, Gang Chen, Fanchao Qi, Minjia Zhang, Baobao Chang, Maosong Sun
2025	J	`jnl`	Aha Moment Revisited: Are VLMs Truly Capable of Self Verification in Inference-time Scaling? CoRR Mingyuan Wu, Meitang Li, Jingcheng Yang, Jize Jiang, Kaizhuo Yan, Zhaoheng Li, Minjia Zhang, Klara Nahrstedt
2025	A*	`conf`	Buffalo: Enabling Large-Scale GNN Training via Memory-Efficient Bucketization. HPCA Shuangyan Yang, Minjia Zhang, Dong Li
2025	J	`jnl`	Cache-of-Thought: Master-Apprentice Framework for Cost-Effective Vision Language Model Inference. CoRR Mingyuan Wu, Jize Jiang, Haozhen Zheng, Meitang Li, Zhaoheng Li, Beitong Tian, Bo Chen, Yongjoo Park, Minjia Zhang, ChengXiang Zhai, Klara Nahrstedt
2025	A*	`conf`	Cache-of-Thought: Master-Apprentice Framework for Cost-Effective Vision Language Model Reasoning. EMNLP Mingyuan Wu, Jize Jiang, Haozhen Zheng, Meitang Li, Zhaoheng Li, Beitong Tian, Bo Chen, Yongjoo Park, Minjia Zhang, ChengXiang Zhai, Klara Nahrstedt
2025	B	`conf`	Degree-Based Scheduling and Memory Management for Large-Scale Exact Online GNN Inference. IEEE Big Data Alireza Namazi, Haiying Shen, Tanmoy Sen, Minjia Zhang
2025	J	`jnl`	FaithLens: Detecting and Explaining Faithfulness Hallucination. CoRR Shuzheng Si, Qingyi Wang, Haozhe Zhao, Yuzhuo Bai, Guanqiao Chen, Kangyang Luo, Gang Chen, Fanchao Qi, Minjia Zhang, Baobao Chang, Maosong Sun
2025	J	`jnl`	FedCust: Offloading hyperparameter customization for federated learning. Perform. Evaluation Syed Zawad, Xiaolong Ma, Jun Yi, Cheng Li, Minjia Zhang, Lei Yang, Feng Yan, Yuxiong He
2025	A*	`conf`	FlexGaussian: Flexible and Cost-Effective Training-Free Compression for 3D Gaussian Splatting. ACM Multimedia Boyuan Tian, Qizhe Gao, Siran Xianyu, Xiaotong Cui, Minjia Zhang
2025	J	`jnl`	FlexGaussian: Flexible and Cost-Effective Training-Free Compression for 3D Gaussian Splatting. CoRR Boyuan Tian, Qizhe Gao, Siran Xianyu, Xiaotong Cui, Minjia Zhang
2025	J	`jnl`	InstantEdit: Text-Guided Few-Step Image Editing with Piecewise Rectified Flow. CoRR Yiming Gong, Zhen Zhu, Minjia Zhang
2025	A*	`conf`	Large Language Models as Configuration Validators. ICSE Xinyu Lian, Yinfang Chen, Runxiang Cheng, Jie Huang, Parth Thakkar, Minjia Zhang, Tianyin Xu
2025	A*	`conf`	Looking Beyond Text: Reducing Language Bias in Large Vision-Language Models via Multimodal Dual-Attention and Soft-Image Guidance. EMNLP Haozhe Zhao, Shuzheng Si, Liang Chen, Yichi Zhang, Maosong Sun, Baobao Chang, Minjia Zhang
2025	J	`jnl`	MMGR: Multi-Modal Generative Reasoning. CoRR Zefan Cai, Haoyi Qiu, Tianyi Ma, Haozhe Zhao, Gengze Zhou, Kung-Hsiang Huang, Parisa Kordjamshidi, Minjia Zhang, Wen Xiao, Jiuxiang Gu, Nanyun Peng, Junjie Hu
2025	—	`conf`	MedCite: Can Language Models Generate Verifiable Text for Medicine? ACL (Findings) Xiao Wang, Mengjue Tan, Qiao Jin, Guangzhi Xiong, Yu Hu, Aidong Zhang, Zhiyong Lu, Minjia Zhang
2025	J	`jnl`	MedCite: Can Language Models Generate Verifiable Text for Medicine? CoRR Xiao Wang, Mengjue Tan, Qiao Jin, Guangzhi Xiong, Yu Hu, Aidong Zhang, Zhiyong Lu, Minjia Zhang
2025	J	`jnl`	MegaFold: System-Level Optimizations for Accelerating Protein Structure Prediction Models. CoRR Hoa La, Ahan Gupta, Alex Morehead, Jianlin Cheng, Minjia Zhang
2025	—	`conf`	MiLo: Efficient Quantized MoE Inference with Mixture of Low-Rank Compensators. MLSys Beichen Huang, Yueming Yuan, Zelei Shao, Minjia Zhang
2025	J	`jnl`	MiLo: Efficient Quantized MoE Inference with Mixture of Low-Rank Compensators. CoRR Beichen Huang, Yueming Yuan, Zelei Shao, Minjia Zhang
2025	—	`conf`	MiniKV: Pushing the Limits of 2-Bit KV Cache via Compression and System Co-Design for Efficient Long Context Inference. ACL (Findings) Akshat Sharma, Hangliang Ding, Jianping Li, Neel Dani, Minjia Zhang
2025	A*	`conf`	NetZIP: Algorithm/Hardware Co-design of In-network Lossless Compression for Distributed Large Model Training. MICRO Jinghan Huang, Hyungyo Kim, Nachuan Wang, Jaeyoung Kang, Hrishi Shah, Eun Kyung Lee, Minjia Zhang, Fan Lai, Nam Sung Kim
2025	J	`jnl`	PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference. CoRR Yushu Zhao, Zheng Wang, Minjia Zhang
2025	J	`jnl`	RAG-Gym: Optimizing Reasoning and Search Agents with Process Supervision. CoRR Guangzhi Xiong, Qiao Jin, Xiao Wang, Yin Fang, Haolin Liu, Yifan Yang, Fangyuan Chen, Zhixing Song, Dengyu Wang, Minjia Zhang, Zhiyong Lu, Aidong Zhang
2025	J	`jnl`	RenAIssance: A Survey Into AI Text-to-Image Generation in the Era of Large Model. IEEE Trans. Pattern Anal. Mach. Intell. Fengxiang Bie, Yibo Yang, Zhongzhu Zhou, Adam Ghanem, Minjia Zhang, Zhewei Yao, Xiaoxia Wu, Connor Holmes, Pareesa Ameneh Golnari, David A. Clifton, Yuxiong He, Dacheng Tao, Shuaiwen Leon Song
2025	J	`jnl`	Slow-Fast Policy Optimization: Reposition-Before-Update for LLM Reasoning. CoRR Ziyan Wang, Zheng Wang, Jie Fu, Xingwei Qu, Qi Cheng, Shengpu Tang, Minjia Zhang, Xiaoming Huo
2025	J	`jnl`	SuperOffload: Unleashing the Power of Large-Scale LLM Training on Superchips. CoRR Xinyu Lian, Masahiro Tanaka, Olatunji Ruwase, Minjia Zhang
2025	J	`jnl`	Teaching Large Language Models to Maintain Contextual Faithfulness via Synthetic Tasks and Reinforcement Learning. CoRR Shuzheng Si, Haozhe Zhao, Cheng Gao, Yuzhuo Bai, Zhitong Wang, Bofei Gao, Kangyang Luo, Wenhao Li, Yufei Huang, Gang Chen, Fanchao Qi, Minjia Zhang, Baobao Chang, Maosong Sun
2025	Misc	`conf`	Toward Sensor-In-the-Loop LLM Agent: Benchmarks and Implications. SenSys Zhiwei Ren, Junbo Li, Minjia Zhang, Di Wang, Xiaoran Fan, Longfei Shangguan
2025	—	`conf`	Universal Checkpointing: A Flexible and Efficient Distributed Checkpointing System for Large-Scale DNN Training with Reconfigurable Parallelism. USENIX ATC Xinyu Lian, Sam Ade Jacobs, Lev Kurilenko, Masahiro Tanaka, Stas Bekman, Olatunji Ruwase, Minjia Zhang
2025	A*	`conf`	VQ-LLM: High-performance Code Generation for Vector Quantization Augmented LLM Inference. HPCA Zihan Liu, Xinhao Luo, Junxian Guo, Wentao Ni, Yangjie Zhou, Yue Guan, Cong Guo, Weihao Cui, Yu Feng, Minyi Guo, Yuhao Zhu, Minjia Zhang, Chen Jin, Jingwen Leng
2025	J	`jnl`	VQ-LLM: High-performance Code Generation for Vector Quantization Augmented LLM Inference. CoRR Zihan Liu, Xinhao Luo, Junxian Guo, Wentao Ni, Yangjie Zhou, Yue Guan, Cong Guo, Weihao Cui, Yu Feng, Minyi Guo, Yuhao Zhu, Minjia Zhang, Jingwen Leng, Chen Jin
2025	J	`jnl`	VTool-R1: VLMs Learn to Think with Images via Reinforcement Learning on Multimodal Tool Use. CoRR Mingyuan Wu, Jingcheng Yang, Jize Jiang, Meitang Li, Kaizhuo Yan, Hanchao Yu, Minjia Zhang, ChengXiang Zhai, Klara Nahrstedt
2025	J	`jnl`	VecFlow: A High-Performance Vector Data Management System for Filtered-Search on GPUs. CoRR Jingyi Xi, Chenghao Mo, Benjamin Karsin, Artem M. Chirkin, Mingqin Li, Minjia Zhang
2025	J	`jnl`	VecFlow: A High-Performance Vector Data Management System for Filtered-Search on GPUs. Proc. ACM Manag. Data Jingyi Xi, Chenghao Mo, Ben Karsin, Artem M. Chirkin, Mingqin Li, Minjia Zhang
2025	J	`jnl`	VoltanaLLM: Feedback-Driven Frequency Control and State-Space Routing for Energy-Efficient LLM Serving. CoRR Jiahuan Yu, Aryan Taneja, Junfeng Lin, Minjia Zhang
2025	A	`conf`	X-MoE: Enabling Scalable Training for Emerging Mixture-of-Experts Architectures on HPC Platforms. SC Yueming Yuan, Ahan Gupta, Jianping Li, Sajal Dash, Feiyi Wang, Minjia Zhang
2025	J	`jnl`	X-MoE: Enabling Scalable Training for Emerging Mixture-of-Experts Architectures on HPC Platforms. CoRR Yueming Yuan, Ahan Gupta, Jianping Li, Sajal Dash, Feiyi Wang, Minjia Zhang
2024	J	`jnl`	Computing in the Era of Large Generative Models: From Cloud-Native to AI-Native. CoRR Yao Lu, Song Bian, Lequn Chen, Yongjun He, Yulong Hui, Matthew Lentz, Beibin Li, Fei Liu, Jialin Li, Qi Liu, Rui Liu, Xiaoxuan Liu, Lin Ma, Kexin Rong, Jianguo Wang, Yingjun Wu, Yongji Wu, Huanchen Zhang, Minjia Zhang, Qizhen Zhang, Tianyi Zhou, Danyang Zhuo
2024	A*	`conf`	DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing. AAAI Conglong Li, Zhewei Yao, Xiaoxia Wu, Minjia Zhang, Connor Holmes, Cheng Li, Yuxiong He
2024	J	`jnl`	Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questions. CoRR Guangzhi Xiong, Qiao Jin, Xiao Wang, Minjia Zhang, Zhiyong Lu, Aidong Zhang
2024	J	`jnl`	MiniKV: Pushing the Limits of LLM Inference via 2-Bit Layer-Discriminative KV Cache. CoRR Akshat Sharma, Hangliang Ding, Jianping Li, Neel Dani, Minjia Zhang
2024	A*	`conf`	Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs. ICLR Suyu Ge, Yunan Zhang, Liyuan Liu, Minjia Zhang, Jiawei Han, Jianfeng Gao
2024	J	`jnl`	Model Tells You Where to Merge: Adaptive KV Cache Merging for LLMs on Long-Context Tasks. CoRR Zheng Wang, Boxiao Jin, Zhongzhi Yu, Minjia Zhang
2024	J	`jnl`	Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey. CoRR Liang Chen, Zekun Wang, Shuhuai Ren, Lei Li, Haozhe Zhao, Yunshui Li, Zefan Cai, Hongcheng Guo, Lei Zhang, Yizhe Xiong, Yichi Zhang, Ruoyu Wu, Qingxiu Dong, Ge Zhang, Jian Yang, Lingwei Meng, Shujie Hu, Yulong Chen, Junyang Lin, Shuai Bai, Andreas Vlachos, Xu Tan, Minjia Zhang, Wen Xiao, Aaron Yee, Tianyu Liu, Baobao Chang
2024	Misc	`conf`	Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances. NSDI Jiangfei Duan, Ziang Song, Xupeng Miao, Xiaoli Xi, Dahua Lin, Harry Xu, Minjia Zhang, Zhihao Jia
2024	J	`jnl`	Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances. CoRR Jiangfei Duan, Ziang Song, Xupeng Miao, Xiaoli Xi, Dahua Lin, Harry Xu, Minjia Zhang, Zhihao Jia
2024	J	`jnl`	Stochastic Monkeys at Play: Random Augmentations Cheaply Break LLM Safety Alignment. CoRR Jason Vega, Junsheng Huang, Gaokai Zhang, Hangoo Kang, Minjia Zhang, Gagandeep Singh
2024	—	`conf`	System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. IPDPS (Workshops) Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Reza Yazdani Aminabadi, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He
2024	A*	`conf`	System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. PODC Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Reza Yazdani Aminadabi, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He
2024	J	`jnl`	Transforming the Hybrid Cloud for Emerging AI Workloads. CoRR Deming Chen, Alaa Youssef, Ruchi Pendse, André Schleife, Bryan K. Clark, Hendrik F. Hamann, Jingrui He, Teodoro Laino, Lav R. Varshney, Yuxiong Wang, Avirup Sil, Reyhaneh Jabbarvand, Tianyin Xu, Volodymyr V. Kindratenko, Carlos H. A. Costa, Sarita V. Adve, Charith Mendis, Minjia Zhang, Santiago Núñez-Corrales, Raghu K. Ganti, Mudhakar Srivatsa, Nam Sung Kim, Josep Torrellas, Jian Huang, Seetharami R. Seelam, Klara Nahrstedt, Tarek F. Abdelzaher, Tamar Eilam, Huimin Zhao, Matteo Manica, Ravishankar K. Iyer, Martin Hirzel, Vikram S. Adve, Darko Marinov, Hubertus Franke, Hanghang Tong, Elizabeth A. Ainsworth, Han Zhao, Deepak Vasisht, Minh Do, Fábio Oliveira, Giovanni Pacifici, Ruchir Puri, Priya Nagpurkar
2024	A*	`conf`	UltraEdit: Instruction-based Fine-Grained Image Editing at Scale. NeurIPS Haozhe Zhao, Xiaojian (Shawn) Ma, Liang Chen, Shuzheng Si, Rujie Wu, Kaikai An, Peiyu Yu, Minjia Zhang, Qing Li, Baobao Chang
2024	J	`jnl`	UltraEdit: Instruction-based Fine-Grained Image Editing at Scale. CoRR Haozhe Zhao, Xiaojian Ma, Liang Chen, Shuzheng Si, Rujie Wu, Kaikai An, Peiyu Yu, Minjia Zhang, Qing Li, Baobao Chang
2024	J	`jnl`	Universal Checkpointing: Efficient and Flexible Checkpointing for Large Scale Distributed Training. CoRR Xinyu Lian, Sam Ade Jacobs, Lev Kurilenko, Masahiro Tanaka, Stas Bekman, Olatunji Ruwase, Minjia Zhang
2024	J	`jnl`	Vexless: A Serverless Vector Data Management System Using Cloud Functions. Proc. ACM Manag. Data Yongye Su, Yinqi Sun, Minjia Zhang, Jianguo Wang
2023	Misc	`conf`	Bamboo: Making Preemptible Instances Resilient for Affordable Training of Large DNNs. NSDI John Thorpe, Pengzhan Zhao, Jonathan Eyolfson, Yifan Qiao, Zhihao Jia, Minjia Zhang, Ravi Netravali, Guoqing Harry Xu
2023	—	`conf`	Betty: Enabling Large-Scale GNN Training with Batch-Level Graph Partitioning. ASPLOS (2) Shuangyan Yang, Minjia Zhang, Wenqian Dong, Dong Li
2023	A*	`conf`	Cost-effective On-device Continual Learning over Memory Hierarchy with Miro. MobiCom Xinyue Ma, Suyeon Jeong, Minjia Zhang, Di Wang, Jonghyun Choi, Myeongjae Jeon
2023	J	`jnl`	Cost-effective On-device Continual Learning over Memory Hierarchy with Miro. CoRR Xinyue Ma, Suyeon Jeong, Minjia Zhang, Di Wang, Jonghyun Choi, Myeongjae Jeon
2023	J	`jnl`	DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. CoRR Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He
2023	J	`jnl`	DeepSpeed-Chat: Easy, Fast and Affordable RLHF Training of ChatGPT-like Models at All Scales. CoRR Zhewei Yao, Reza Yazdani Aminabadi, Olatunji Ruwase, Samyam Rajbhandari, Xiaoxia Wu, Ammar Ahmad Awan, Jeff Rasley, Minjia Zhang, Conglong Li, Connor Holmes, Zhongzhu Zhou, Michael Wyatt, Molly Smith, Lev Kurilenko, Heyang Qin, Masahiro Tanaka, Shuai Che, Shuaiwen Leon Song, Yuxiong He
2023	J	`jnl`	DeepSpeed-VisualChat: Multi-Round Multi-Image Interleave Chat via Multi-Modal Causal Attention. CoRR Zhewei Yao, Xiaoxia Wu, Conglong Li, Minjia Zhang, Heyang Qin, Olatunji Ruwase, Ammar Ahmad Awan, Samyam Rajbhandari, Yuxiong He
2023	J	`jnl`	DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl W. Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
2023	J	`jnl`	FedHC: A Scalable Federated Learning Framework for Heterogeneous and Resource-Constrained Clients. CoRR Min Zhang, Fuxun Yu, Yongbo Yu, Minjia Zhang, Ang Li, Xiang Chen
2023	A*	`conf`	Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam. ICLR Yucheng Lu, Conglong Li, Minjia Zhang, Christopher De Sa, Yuxiong He
2023	J	`jnl`	Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs. CoRR Suyu Ge, Yunan Zhang, Liyuan Liu, Minjia Zhang, Jiawei Han, Jianfeng Gao
2023	J	`jnl`	RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model. CoRR Fengxiang Bie, Yibo Yang, Zhongzhu Zhou, Adam Ghanem, Minjia Zhang, Zhewei Yao, Xiaoxia Wu, Connor Holmes, Pareesa Ameneh Golnari, David A. Clifton, Yuxiong He, Dacheng Tao, Shuaiwen Leon Song
2023	A	`conf`	Revisiting the Efficiency-Accuracy Tradeoff in Adapting Transformer Models via Adversarial Fine-Tuning. ECAI Minjia Zhang, Uma-Naresh Niranjan, Yuxiong He
2023	J	`jnl`	SHARP: An Adaptable, Energy-Efficient Accelerator for Recurrent Neural Networks. ACM Trans. Embed. Comput. Syst. Reza Yazdani Aminabadi, Olatunji Ruwase, Minjia Zhang, Yuxiong He, José-María Arnau, Antonio González
2023	B	`conf`	iQAN: Fast and Accurate Vector Search with Efficient Intra-Query Parallelism on Multi-Core Architectures. PPoPP Zhen Peng, Minjia Zhang, Kai Li, Ruoming Jin, Bin Ren
2023	J	`jnl`	iQAN: Fast and Accurate Vector Search with Efficient Intra-Query Parallelism on Multi-Core Architectures. IEEE Data Eng. Bull. Minjia Zhang, Jie Ren, Zhen Peng, Ruoming Jin, Dong Li, Bin Ren
2022	J	`jnl`	A Survey of Multi-Tenant Deep Learning Inference on GPU. CoRR Fuxun Yu, Di Wang, Longfei Shangguan, Minjia Zhang, Chenchen Liu, Xiang Chen
2022	A*	`conf`	Adversarial Data Augmentation for Task-Specific Knowledge Distillation of Pre-trained Transformers. AAAI Minjia Zhang, Uma-Naresh Niranjan, Yuxiong He
2022	J	`jnl`	Bamboo: Making Preemptible Instances Resilient for Affordable Training of Large DNNs. CoRR John Thorpe, Pengzhan Zhao, Jonathan Eyolfson, Yifan Qiao, Zhihao Jia, Minjia Zhang, Ravi Netravali, Guoqing Harry Xu
2022	A*	`conf`	CarM: hierarchical episodic memory for continual learning. DAC Soobee Lee, Minindu Weerakoon, Jonghyun Choi, Minjia Zhang, Di Wang, Myeongjae Jeon
2022	J	`jnl`	Compressing Pre-trained Transformers via Low-Bit NxM Sparsity for Natural Language Understanding. CoRR Connor Holmes, Minjia Zhang, Yuxiong He, Bo Wu
2022	J	`jnl`	DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing. CoRR Conglong Li, Zhewei Yao, Xiaoxia Wu, Minjia Zhang, Connor Holmes, Cheng Li, Yuxiong He
2022	J	`jnl`	DeepSpeed Inference: Enabling Efficient Inference of Transformer Models at Unprecedented Scale. CoRR Reza Yazdani Aminabadi, Samyam Rajbhandari, Minjia Zhang, Ammar Ahmad Awan, Cheng Li, Du Li, Elton Zheng, Jeff Rasley, Shaden Smith, Olatunji Ruwase, Yuxiong He
2022	A	`conf`	DeepSpeed- Inference: Enabling Efficient Inference of Transformer Models at Unprecedented Scale. SC Reza Yazdani Aminabadi, Samyam Rajbhandari, Ammar Ahmad Awan, Cheng Li, Du Li, Elton Zheng, Olatunji Ruwase, Shaden Smith, Minjia Zhang, Jeff Rasley, Yuxiong He
2022	A*	`conf`	DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale. ICML Samyam Rajbhandari, Conglong Li, Zhewei Yao, Minjia Zhang, Reza Yazdani Aminabadi, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He
2022	J	`jnl`	DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale. CoRR Samyam Rajbhandari, Conglong Li, Zhewei Yao, Minjia Zhang, Reza Yazdani Aminabadi, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He
2022	J	`jnl`	Extreme Compression for Pre-trained Transformers Made Simple and Efficient. CoRR Xiaoxia Wu, Zhewei Yao, Minjia Zhang, Conglong Li, Yuxiong He
2022	A	`conf`	GraSP: Optimizing Graph-based Nearest Neighbor Search with Subgraph Sampling and Pruning. WSDM Minjia Zhang, Wenhan Wang, Yuxiong He
2022	J	`jnl`	Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam. CoRR Yucheng Lu, Conglong Li, Minjia Zhang, Christopher De Sa, Yuxiong He
2022	—	`conf`	Powering Multi-Task Federated Learning with Competitive GPU Resource Sharing. WWW (Companion Volume) Yongbo Yu, Fuxun Yu, Zirui Xu, Di Wang, Minjia Zhang, Ang Li, Shawn Bray, Chenchen Liu, Xiang Chen
2022	J	`jnl`	Random-LTD: Random and Layerwise Token Dropping Brings Efficient Training for Large-scale Transformers. CoRR Zhewei Yao, Xiaoxia Wu, Conglong Li, Connor Holmes, Minjia Zhang, Cheng Li, Yuxiong He
2022	J	`jnl`	ScaLA: Accelerating Adaptation of Pre-Trained Transformer-Based Language Models via Efficient Large-Batch Adversarial Noise. CoRR Minjia Zhang, Uma-Naresh Niranjan, Yuxiong He
2022	J	`jnl`	Speed-ANN: Low-Latency and High-Accuracy Nearest Neighbor Search via Intra-Query Parallelism. CoRR Zhen Peng, Minjia Zhang, Kai Li, Ruoming Jin, Bin Ren
2022	A*	`conf`	The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models. NeurIPS Conglong Li, Minjia Zhang, Yuxiong He
2022	A*	`conf`	XTC: Extreme Compression for Pre-trained Transformers Made Simple and Efficient. NeurIPS Xiaoxia Wu, Zhewei Yao, Minjia Zhang, Conglong Li, Yuxiong He
2022	A*	`conf`	ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers. NeurIPS Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, Xiaoxia Wu, Conglong Li, Yuxiong He
2022	J	`jnl`	ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers. CoRR Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, Xiaoxia Wu, Conglong Li, Yuxiong He
2021	J	`jnl`	A Survey of Large-Scale Deep Learning Serving System Optimization: Challenges and Opportunities. CoRR Fuxun Yu, Di Wang, Longfei Shangguan, Minjia Zhang, Xulong Tang, Chenchen Liu, Xiang Chen
2021	J	`jnl`	Carousel Memory: Rethinking the Design of Episodic Memory for Continual Learning. CoRR Soobee Lee, Minindu Weerakoon, Jonghyun Choi, Minjia Zhang, Di Wang, Myeongjae Jeon
2021	J	`jnl`	Curriculum Learning: A Regularization Method for Efficient and Stable Billion-Scale GPT Model Pre-Training. CoRR Conglong Li, Minjia Zhang, Yuxiong He
2021	—	`conf`	DL Inference and Training Optimization Towards Speed and Scale. WWW (Companion Volume) Minjia Zhang
2021	A	`conf`	DUET: A Compiler-Runtime Subgraph Scheduling Approach for Tensor Programs on a Coupled CPU-GPU Architecture. IPDPS Minjia Zhang, Zehua Hu, Mingqin Li
2021	A*	`conf`	DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation. ICLR Minjia Zhang, Menghao Li, Chi Wang, Mingqin Li
2021	A*	`conf`	NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM. NeurIPS Connor Holmes, Minjia Zhang, Yuxiong He, Bo Wu
2021	J	`jnl`	NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM. CoRR Connor Holmes, Minjia Zhang, Yuxiong He, Bo Wu
2021	A*	`conf`	Sentinel: Efficient Tensor Migration and Allocation on Heterogeneous Memory Systems for Deep Learning. HPCA Jie Ren, Jiaolin Luo, Kai Wu, Minjia Zhang, Hyeran Jeon, Dong Li
2021	J	`jnl`	Understanding and Generalizing Monotonic Proximity Graphs for Approximate Nearest Neighbor Search. CoRR Dantong Zhu, Minjia Zhang
2021	A	`conf`	Vertical Scaling of Resource for OpenMP Application. ICSOC Junfeng Zhao, Minjia Zhang, Hongji Yang
2021	—	`conf`	ZeRO-Offload: Democratizing Billion-Scale Model Training. USENIX ATC Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, Olatunji Ruwase, Shuangyan Yang, Minjia Zhang, Dong Li, Yuxiong He
2021	J	`jnl`	ZeRO-Offload: Democratizing Billion-Scale Model Training. CoRR Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, Olatunji Ruwase, Shuangyan Yang, Minjia Zhang, Dong Li, Yuxiong He
2020	A*	`conf`	Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping. NeurIPS Minjia Zhang, Yuxiong He
2020	J	`jnl`	Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping. CoRR Minjia Zhang, Yuxiong He
2020	A*	`conf`	AdaTune: Adaptive Tensor Program Compilation Made Efficient. NeurIPS Menghao Li, Minjia Zhang, Chi Wang, Mingqin Li
2020	A*	`conf`	HM-ANN: Efficient Billion-Point Nearest Neighbor Search on Heterogeneous Memory. NeurIPS Jie Ren, Minjia Zhang, Dong Li
2020	—	`conf`	Improving Approximate Nearest Neighbor Search through Learned Adaptive Early Termination. SIGMOD Conference Conglong Li, Minjia Zhang, David G. Andersen, Yuxiong He
2019	—	`conf`	Accelerating Large Scale Deep Learning Inference through DeepCPU at Microsoft. OpML Minjia Zhang, Samyam Rajbhandari, Wenhan Wang, Elton Zheng, Olatunji Ruwase, Jeff Rasley, Jason Li, Junhua Wang, Yuxiong He
2019	—	`conf`	Code Refactoring from OpenMP to MapReduce Model for Big Data Processing. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI Junfeng Zhao, Minjia Zhang, Hongji Yang
2019	A	`conf`	GRIP: Multi-Store Capacity-Optimized High-Performance Nearest Neighbor Search for Vector Search Engine. CIKM Minjia Zhang, Yuxiong He
2019	J	`jnl`	LSTM-Sharp: An Adaptable, Energy-Efficient Hardware Accelerator for Long Short-Term Memory. CoRR Reza Yazdani, Olatunji Ruwase, Minjia Zhang, Yuxiong He, José-María Arnau, Antonio González
2019	J	`jnl`	Sentinel: Runtime Data Management on Heterogeneous Main MemorySystems for Deep Learning. CoRR Jie Ren, Jiaolin Luo, Kai Wu, Minjia Zhang, Dong Li
2018	—	`conf`	DeepCPU: Serving RNN-based Deep Learning Models 10x Faster. USENIX ATC Minjia Zhang, Samyam Rajbhandari, Wenhan Wang, Yuxiong He
2018	—	`conf`	Learning Intrinsic Sparse Structures within Long Short-Term Memory. ICLR (Poster) Wei Wen, Yuxiong He, Samyam Rajbhandari, Minjia Zhang, Wenhan Wang, Fang Liu, Bin Hu, Yiran Chen, Hai Li
2018	A*	`conf`	Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models. NeurIPS Minjia Zhang, Wenhan Wang, Xiaodong Liu, Jianfeng Gao, Yuxiong He
2018	J	`jnl`	Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models. CoRR Minjia Zhang, Xiaodong Liu, Wenhan Wang, Jianfeng Gao, Yuxiong He
2018	—	`conf`	Refactoring OpenMP Code Based on MapReduce Model. ISPA/IUCC/BDCloud/SocialCom/SustainCom Junfeng Zhao, Minjia Zhang
2018	J	`jnl`	Zoom: SSD-based Vector Search for Optimizing Accuracy, Latency and Memory. CoRR Minjia Zhang, Yuxiong He
2017	C	`conf`	Avoiding consistency exceptions under strong memory models. ISMM Minjia Zhang, Swarnendu Biswas, Michael D. Bond
2017	J	`jnl`	Hybridizing and Relaxing Dependence Tracking for Efficient Parallel Runtime Support. ACM Trans. Parallel Comput. Man Cao, Minjia Zhang, Aritra Sengupta, Swarnendu Biswas, Michael D. Bond
2017	B	`conf`	Lightweight data race detection for production runs. CC Swarnendu Biswas, Man Cao, Minjia Zhang, Michael D. Bond, Benjamin P. Wood
2017	B	`conf`	POSTER: On the Problem of Consistency Exceptions in the Context of Strong Memory Models. PPoPP Minjia Zhang, Swarnendu Biswas, Michael D. Bond
2016	B	`conf`	Drinking from both glasses: combining pessimistic and optimistic tracking of cross-thread dependences. PPoPP Man Cao, Minjia Zhang, Aritra Sengupta, Michael D. Bond
2016	B	`conf`	Relaxed dependence tracking for parallel runtime support. CC Minjia Zhang, Swarnendu Biswas, Michael D. Bond
2015	A*	`conf`	Hybrid Static: Dynamic Analysis for Statically Bounded Region Serializability. ASPLOS Aritra Sengupta, Swarnendu Biswas, Minjia Zhang, Michael D. Bond, Milind Kulkarni
2015	B	`conf`	Low-overhead software transactional memory with progress guarantees and strong semantics. PPoPP Minjia Zhang, Jipeng Huang, Man Cao, Michael D. Bond
2015	—	`conf`	SIRe: an efficient snapshot isolation-based memory model for detecting and tolerating region conflicts. SPLASH (Companion Volume) Minjia Zhang
2015	A	`conf`	Valor: efficient, software-only region conflict exceptions. OOPSLA Swarnendu Biswas, Minjia Zhang, Michael D. Bond, Brandon Lucia
2013	A	`conf`	OCTET: capturing and controlling cross-thread dependences efficiently. OOPSLA Michael D. Bond, Milind Kulkarni, Man Cao, Minjia Zhang, Meisam Fathi Salmi, Swarnendu Biswas, Aritra Sengupta, Jipeng Huang
2011	B	`conf`	Memcached Design on High Performance RDMA Capable Interconnects. ICPP Jithin Jose, Hari Subramoni, Miao Luo, Minjia Zhang, Jian Huang, Md. Wasi-ur-Rahman, Nusrat S. Islam, Xiangyong Ouyang, Hao Wang, Sayantan Sur, Dhabaleswar K. Panda
2010	B	`conf`	VirtCFT: A Transparent VM-Level Fault-Tolerant System for Virtual Clusters. ICPADS Minjia Zhang, Hai Jin, Xuanhua Shi, Song Wu