Mu Li - RankMe

101 papers A* 19A 5B 1Journal 63Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Back to Basics: Revisiting ASR in the Age of Voice Agents. CoRR Geeyang Tay, Wentao Ma, Jaewon Lee, Yuzhi Tang, Daniel Lee, Weisu Yin, Dongming Shen, Silin Meng, Yi Zhu, Mu Li, Alex Smola
2025	J	`jnl`	EmergentTTS-Eval: Evaluating TTS Models on Complex Prosodic, Expressiveness, and Linguistic Challenges Using Model-as-a-Judge. CoRR Ruskin Raj Manku, Yuzhi Tang, Xingjian Shi, Mu Li, Alex Smola
2025	J	`jnl`	RPGBENCH: Evaluating Large Language Models as Role-Playing Game Engines. CoRR Pengfei Yu, Dongming Shen, Silin Meng, Jaewon Lee, Weisu Yin, Andrea Yaoyun Cui, Zhenlin Xu, Yi Zhu, Xingjian Shi, Mu Li, Alex Smola
2024	J	`jnl`	Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift. J. Data-centric Mach. Learn. Res. Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li
2024	J	`jnl`	Improving Semantic Segmentation via Efficient Self-Training. IEEE Trans. Pattern Anal. Mach. Intell. Yi Zhu, Zhongyue Zhang, Chongruo Wu, Zhi Zhang, Tong He, Hang Zhang, R. Manmatha, Mu Li, Alexander J. Smola
2024	J	`jnl`	Multimodal Chain-of-Thought Reasoning in Language Models. Trans. Mach. Learn. Res. Zhuosheng Zhang, Aston Zhang, Mu Li, Hai Zhao, George Karypis, Alex Smola
2024	J	`jnl`	Online learning from capricious data streams via shared and new feature spaces. Appl. Intell. Peng Zhou, Shuai Zhang, Mu Li, Yuanting Yan
2023	A*	`conf`	A Cheaper and Better Diffusion Language Model with Soft-Masked Noise. EMNLP Jiaao Chen, Aston Zhang, Mu Li, Alex Smola, Diyi Yang
2023	J	`jnl`	A Cheaper and Better Diffusion Language Model with Soft-Masked Noise. CoRR Jiaao Chen, Aston Zhang, Mu Li, Alex Smola, Diyi Yang
2023	A*	`conf`	AIM: Adapting Image Models for Efficient Video Action Recognition. ICLR Taojiannan Yang, Yi Zhu, Yusheng Xie, Aston Zhang, Chen Chen, Mu Li
2023	J	`jnl`	AIM: Adapting Image Models for Efficient Video Action Recognition. CoRR Taojiannan Yang, Yi Zhu, Yusheng Xie, Aston Zhang, Chen Chen, Mu Li
2023	A*	`conf`	Automatic Chain of Thought Prompting in Large Language Models. ICLR Zhuosheng Zhang, Aston Zhang, Mu Li, Alex Smola
2023	J	`jnl`	GFM: Building Geospatial Foundation Models via Continual Pretraining. CoRR Matías Mendieta, Boran Han, Xingjian Shi, Yi Zhu, Chen Chen, Mu Li
2023	J	`jnl`	LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation. CoRR Jiaxin Cheng, Xiao Liang, Xingjian Shi, Tong He, Tianjun Xiao, Mu Li
2023	A*	`conf`	Learning Multimodal Data Augmentation in Feature Space. ICLR Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson
2023	—	`conf`	MixGen: A New Multi-Modal Data Augmentation. WACV (Workshops) Xiaoshuai Hao, Yi Zhu, Srikar Appalaraju, Aston Zhang, Wanqian Zhang, Bo Li, Mu Li
2023	J	`jnl`	Multimodal Chain-of-Thought Reasoning in Language Models. CoRR Zhuosheng Zhang, Aston Zhang, Mu Li, Hai Zhao, George Karypis, Alex Smola
2023	A*	`conf`	Parameter-Efficient Fine-Tuning Design Spaces. ICLR Jiaao Chen, Aston Zhang, Xingjian Shi, Mu Li, Alex Smola, Diyi Yang
2023	J	`jnl`	Parameter-Efficient Fine-Tuning Design Spaces. CoRR Jiaao Chen, Aston Zhang, Xingjian Shi, Mu Li, Alex Smola, Diyi Yang
2023	A*	`conf`	PreDiff: Precipitation Nowcasting with Latent Diffusion Models. NeurIPS Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang
2023	J	`jnl`	PreDiff: Precipitation Nowcasting with Latent Diffusion Models. CoRR Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang
2023	A*	`conf`	Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition. NeurIPS Shuhuai Ren, Aston Zhang, Yi Zhu, Shuai Zhang, Shuai Zheng, Mu Li, Alexander J. Smola, Xu Sun
2023	J	`jnl`	Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition. CoRR Shuhuai Ren, Aston Zhang, Yi Zhu, Shuai Zhang, Shuai Zheng, Mu Li, Alex Smola, Xu Sun
2023	J	`jnl`	RAF: Holistic Compilation for Deep Learning Model Training. CoRR Cody Hao Yu, Haozheng Fan, Guangtai Huang, Zhen Jia, Yizhi Liu, Jie Wang, Zach Zheng, Yuan Zhou, Haichen Shen, Junru Shao, Mu Li, Yida Wang
2023	—	`conf`	Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation. ACL (1) Yuxin Ren, Zihan Zhong, Xingjian Shi, Yi Zhu, Chun Yuan, Mu Li
2023	J	`jnl`	Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation. CoRR Yuxin Ren, Zihan Zhong, Xingjian Shi, Yi Zhu, Chun Yuan, Mu Li
2023	J	`jnl`	What Makes for Good Tokenizers in Vision Transformer? IEEE Trans. Pattern Anal. Mach. Intell. Shengju Qian, Yi Zhu, Wenbo Li, Mu Li, Jiaya Jia
2023	A*	`conf`	XTab: Cross-table Pretraining for Tabular Transformers. ICML Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li, George Karypis, Mahsa Shoaran
2023	J	`jnl`	XTab: Cross-table Pretraining for Tabular Transformers. CoRR Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li, George Karypis, Mahsa Shoaran
2022	J	`jnl`	Are Multimodal Models Robust to Image and Text Perturbations? CoRR Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li
2022	J	`jnl`	Automatic Chain of Thought Prompting in Large Language Models. CoRR Zhuosheng Zhang, Aston Zhang, Mu Li, Alex Smola
2022	—	`conf`	BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training. CVPR Workshops Likun Cai, Zhi Zhang, Yi Zhu, Li Zhang, Mu Li, Xiangyang Xue
2022	J	`jnl`	BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training. CoRR Likun Cai, Zhi Zhang, Yi Zhu, Li Zhang, Mu Li, Xiangyang Xue
2022	A*	`conf`	Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. NeurIPS Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung
2022	J	`jnl`	Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. CoRR Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung
2022	J	`jnl`	Learning Multimodal Data Augmentation in Feature Space. CoRR Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson
2022	J	`jnl`	MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud. CoRR Zhen Zhang, Shuai Zheng, Yida Wang, Justin Chiu, George Karypis, Trishul Chilimbi, Mu Li, Xin Jin
2022	J	`jnl`	MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud. Proc. VLDB Endow. Zhen Zhang, Shuai Zheng, Yida Wang, Justin Chiu, George Karypis, Trishul Chilimbi, Mu Li, Xin Jin
2022	J	`jnl`	MixGen: A New Multi-Modal Data Augmentation. CoRR Xiaoshuai Hao, Yi Zhu, Srikar Appalaraju, Aston Zhang, Wanqian Zhang, Bo Li, Mu Li
2022	A*	`conf`	Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition. ICML Haotao Wang, Aston Zhang, Yi Zhu, Shuai Zheng, Mu Li, Alex J. Smola, Zhangyang Wang
2022	J	`jnl`	Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition. CoRR Haotao Wang, Aston Zhang, Yi Zhu, Shuai Zheng, Mu Li, Alex Smola, Zhangyang Wang
2022	A*	`conf`	Removing Batch Normalization Boosts Adversarial Training. ICML Haotao Wang, Aston Zhang, Shuai Zheng, Xingjian Shi, Mu Li, Zhangyang Wang
2022	J	`jnl`	Removing Batch Normalization Boosts Adversarial Training. CoRR Haotao Wang, Aston Zhang, Shuai Zheng, Xingjian Shi, Mu Li, Zhangyang Wang
2022	—	`conf`	ResNeSt: Split-Attention Networks. CVPR Workshops Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Haibin Lin, Zhi Zhang, Yue Sun, Tong He, Jonas Mueller, R. Manmatha, Mu Li, Alexander J. Smola
2022	J	`jnl`	SPT: Semi-Parametric Prompt Tuning for Multitask Prompted Learning. CoRR M. Saiful Bari, Aston Zhang, Shuai Zheng, Xingjian Shi, Yi Zhu, Shafiq Joty, Mu Li
2022	J	`jnl`	Visual Prompt Tuning for Test-time Domain Adaptation. CoRR Yunhe Gao, Xingjian Shi, Yi Zhu, Hao Wang, Zhiqiang Tang, Xiong Zhou, Mu Li, Dimitris N. Metaxas
2022	J	`jnl`	What Makes for Good Tokenizers in Vision Transformer? CoRR Shengju Qian, Yi Zhu, Wenbo Li, Mu Li, Jiaya Jia
2021	—	`conf`	A Unified Efficient Pyramid Transformer for Semantic Segmentation. ICCVW Fangrui Zhu, Yi Zhu, Li Zhang, Chongruo Wu, Yanwei Fu, Mu Li
2021	J	`jnl`	A Unified Efficient Pyramid Transformer for Semantic Segmentation. CoRR Fangrui Zhu, Yi Zhu, Li Zhang, Chongruo Wu, Yanwei Fu, Mu Li
2021	—	`conf`	Benchmarking Multimodal AutoML for Tabular Data with Text Fields. NeurIPS Datasets and Benchmarks Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola
2021	J	`jnl`	Benchmarking Multimodal AutoML for Tabular Data with Text Fields. CoRR Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola
2021	A*	`conf`	Blending Anti-Aliasing into Vision Transformer. NeurIPS Shengju Qian, Hao Shao, Yi Zhu, Mu Li, Jiaya Jia
2021	J	`jnl`	Blending Anti-Aliasing into Vision Transformer. CoRR Shengju Qian, Hao Shao, Yi Zhu, Mu Li, Jiaya Jia
2021	A*	`conf`	CrossNorm and SelfNorm for Generalization under Distribution Shifts. ICCV Zhiqiang Tang, Yunhe Gao, Yi Zhu, Zhi Zhang, Mu Li, Dimitris N. Metaxas
2021	—	`conf`	Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. SustaiNLP@EMNLP Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis
2021	J	`jnl`	Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. CoRR Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis
2021	J	`jnl`	Dive into Deep Learning. CoRR Aston Zhang, Zachary C. Lipton, Mu Li, Alexander J. Smola
2021	—	`conf`	Lorien: Efficient Deep Learning Workloads Delivery. SoCC Cody Hao Yu, Xingjian Shi, Haichen Shen, Zhi Chen, Mu Li, Yida Wang
2021	—	`conf`	Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference. MLSys Haichen Shen, Jared Roesch, Zhi Chen, Wei Chen, Yong Wu, Mu Li, Vin Sharma, Zachary Tatlock, Yida Wang
2021	A*	`conf`	Progressive Coordinate Transforms for Monocular 3D Object Detection. NeurIPS Li Wang, Li Zhang, Yi Zhu, Zhi Zhang, Tong He, Mu Li, Xiangyang Xue
2021	J	`jnl`	Progressive Coordinate Transforms for Monocular 3D Object Detection. CoRR Li Wang, Li Zhang, Yi Zhu, Zhi Zhang, Tong He, Mu Li, Xiangyang Xue
2021	J	`jnl`	SelfNorm and CrossNorm for Out-of-Distribution Robustness. CoRR Zhiqiang Tang, Yunhe Gao, Yi Zhu, Zhi Zhang, Mu Li, Dimitris N. Metaxas
2021	—	`conf`	Video Contrastive Learning with Global Context. ICCVW Haofei Kuang, Yi Zhu, Zhi Zhang, Xinyu Li, Joseph Tighe, Sören Schwertfeger, Cyrill Stachniss, Mu Li
2021	J	`jnl`	Video Contrastive Learning with Global Context. CoRR Haofei Kuang, Yi Zhu, Zhi Zhang, Xinyu Li, Joseph Tighe, Sören Schwertfeger, Cyrill Stachniss, Mu Li
2020	J	`jnl`	A Comprehensive Study of Deep Video Action Recognition. CoRR Yi Zhu, Xinyu Li, Chunhui Liu, Mohammadreza Zolfaghari, Yuanjun Xiong, Chongruo Wu, Zhi Zhang, Joseph Tighe, R. Manmatha, Mu Li
2020	J	`jnl`	Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes. CoRR Shuai Zheng, Haibin Lin, Sheng Zha, Mu Li
2020	J	`jnl`	AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data. CoRR Nick Erickson, Jonas Mueller, Alexander Shirkov, Hang Zhang, Pedro Larroy, Mu Li, Alexander J. Smola
2020	A*	`conf`	CSER: Communication-efficient SGD with Error Reset. NeurIPS Cong Xie, Shuai Zheng, Oluwasanmi Koyejo, Indranil Gupta, Mu Li, Haibin Lin
2020	J	`jnl`	CSER: Communication-efficient SGD with Error Reset. CoRR Cong Xie, Shuai Zheng, Oluwasanmi Koyejo, Indranil Gupta, Mu Li, Haibin Lin
2020	J	`jnl`	FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems. CoRR Yuwei Hu, Zihao Ye, Minjie Wang, Jiali Yu, Da Zheng, Mu Li, Zheng Zhang, Zhiru Zhang, Yida Wang
2020	A	`conf`	FeatGraph: a flexible and efficient backend for graph neural network systems. SC Yuwei Hu, Zihao Ye, Minjie Wang, Jiali Yu, Da Zheng, Mu Li, Zheng Zhang, Zhiru Zhang, Yida Wang
2020	J	`jnl`	GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. J. Mach. Learn. Res. Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng, Yi Zhu
2020	J	`jnl`	Improving Semantic Segmentation via Self-Training. CoRR Yi Zhu, Zhongyue Zhang, Chongruo Wu, Zhi Zhang, Tong He, Hang Zhang, R. Manmatha, Mu Li, Alexander J. Smola
2020	J	`jnl`	Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference. CoRR Haichen Shen, Jared Roesch, Zhi Chen, Wei Chen, Yong Wu, Mu Li, Vin Sharma, Zachary Tatlock, Yida Wang
2020	J	`jnl`	ResNeSt: Split-Attention Networks. CoRR Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Zhi Zhang, Haibin Lin, Yue Sun, Tong He, Jonas Mueller, R. Manmatha, Mu Li, Alexander J. Smola
2019	B	`conf`	A Unified Optimization Approach for CNN Model Inference on Integrated GPUs. ICPP Leyuan Wang, Zhi Chen, Yizhi Liu, Yao Wang, Lianmin Zheng, Mu Li, Yida Wang
2019	J	`jnl`	A Unified Optimization Approach for CNN Model Inference on Integrated GPUs. CoRR Leyuan Wang, Zhi Chen, Yizhi Liu, Yao Wang, Lianmin Zheng, Mu Li, Yida Wang
2019	J	`jnl`	Bag of Freebies for Training Object Detection Neural Networks. CoRR Zhi Zhang, Tong He, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li
2019	A*	`conf`	Bag of Tricks for Image Classification with Convolutional Neural Networks. CVPR Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li
2019	J	`jnl`	Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources. CoRR Haibin Lin, Hang Zhang, Yifei Ma, Tong He, Zhi Zhang, Sheng Zha, Mu Li
2019	J	`jnl`	GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. CoRR Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng
2019	J	`jnl`	Language Models with Transformers. CoRR Chenguang Wang, Mu Li, Alexander J. Smola
2019	J	`jnl`	On the Powerball Method: Variants of Descent Methods for Accelerated Optimization. IEEE Control. Syst. Lett. Ye Yuan, Mu Li, Jun Liu, Claire J. Tomlin
2019	—	`conf`	Optimizing CNN Model Inference on CPUs. USENIX ATC Yizhi Liu, Yao Wang, Ruofei Yu, Mu Li, Vin Sharma, Yida Wang
2018	J	`jnl`	Bag of Tricks for Image Classification with Convolutional Neural Networks. CoRR Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li
2018	J	`jnl`	Optimizing CNN Model Inference on CPUs. CoRR Yizhi Liu, Yao Wang, Ruofei Yu, Mu Li, Vin Sharma, Yida Wang
2017	—	`conf`	Data Driven Resource Allocation for Distributed Learning. AAAI Workshops Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Maria-Florina Balcan, Alexander J. Smola
2017	A	`conf`	Data Driven Resource Allocation for Distributed Learning. AISTATS Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Nina Balcan, Alexander J. Smola
2016	A	`conf`	AdaDelay: Delay Adaptive Distributed Stochastic Optimization. AISTATS Suvrit Sra, Adams Wei Yu, Mu Li, Alexander J. Smola
2016	A	`conf`	DiFacto: Distributed Factorization Machines. WSDM Mu Li, Ziqi Liu, Alexander J. Smola, Yu-Xiang Wang
2016	J	`jnl`	On the Powerball Method. CoRR Ye Yuan, Mu Li, Claire J. Tomlin
2015	J	`jnl`	AdaDelay: Delay Adaptive Distributed Stochastic Convex Optimization. CoRR Suvrit Sra, Adams Wei Yu, Mu Li, Alexander J. Smola
2015	A*	`conf`	Cuckoo Linear Algebra. KDD Li Zhou, David G. Andersen, Mu Li, Alexander J. Smola
2015	J	`jnl`	Data Driven Resource Allocation for Distributed Learning. CoRR Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Maria-Florina Balcan, Alexander J. Smola
2015	J	`jnl`	Empirical Evaluation of Rectified Activations in Convolutional Network. CoRR Bing Xu, Naiyan Wang, Tianqi Chen, Mu Li
2015	J	`jnl`	Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning. CoRR Mu Li, Dave G. Andersen, Alexander J. Smola
2015	A	`conf`	Inferring Movement Trajectories from GPS Snippets. WSDM Mu Li, Amr Ahmed, Alexander J. Smola
2015	J	`jnl`	MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems. CoRR Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, Zheng Zhang
2014	—	`conf`	Communication Efficient Distributed Machine Learning with the Parameter Server. NIPS Mu Li, David G. Andersen, Alexander J. Smola, Kai Yu
2014	A*	`conf`	Efficient mini-batch training for stochastic optimization. KDD Mu Li, Tong Zhang, Yuqiang Chen, Alexander J. Smola
2014	A*	`conf`	Scaling Distributed Machine Learning with the Parameter Server. OSDI Mu Li, David G. Andersen, Jun Woo Park, Alexander J. Smola, Amr Ahmed, Vanja Josifovski, James Long, Eugene J. Shekita, Bor-Yiing Su