Hongyi Wang - RankMe

65 papers A* 17A 1Journal 38Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing. CoRR Wenhao Zheng, Yixiao Chen, Weitong Zhang, Souvik Kundu, Yun Li, Zhengzhong Liu, Eric P. Xing, Hongyi Wang, Huaxiu Yao
2025	J	`jnl`	LLM360 K2: Building a 65B 360-Open-Source Large Language Model from Scratch. CoRR Zhengzhong Liu, Bowen Tan, Hongyi Wang, Willie Neiswanger, Tianhua Tao, Haonan Li, Fajri Koto, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Liqun Ma, Liping Tang, Nikhil Ranjan, Yonghao Zhuang, Guowei He, Renxi Wang, Mingkai Deng, Robin Algayres, Yuanzhi Li, Zhiqiang Shen, Preslav Nakov, Eric P. Xing
2025	—	`conf`	Token Level Routing Inference System for Edge Devices. ACL (3) Jianshu She, Wenhao Zheng, Zhengzhong Liu, Hongyi Wang, Eric P. Xing, Huaxiu Yao, Qirong Ho
2025	J	`jnl`	Token Level Routing Inference System for Edge Devices. CoRR Jianshu She, Wenhao Zheng, Zhengzhong Liu, Hongyi Wang, Eric P. Xing, Huaxiu Yao, Qirong Ho
2024	J	`jnl`	Crystal: Illuminating LLM Abilities on Language and Code. CoRR Tianhua Tao, Junbo Li, Bowen Tan, Hongyi Wang, William Marshall, Bhargav Kanakiya, Joel Hestness, Natalia Vassilieva, Zhiqiang Shen, Eric P. Xing, Zhengzhong Liu
2024	—	`conf`	Does Compressing Activations Help Model Parallel Training? MLSys Song Bian, Dacheng Li, Hongyi Wang, Eric P. Xing, Shivaram Venkataraman
2024	A*	`conf`	FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations. NeurIPS Ziyao Wang, Zheyu Shen, Yexiao He, Guoheng Sun, Hongyi Wang, Lingjuan Lyu, Ang Li
2024	J	`jnl`	FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations. CoRR Ziyao Wang, Zheyu Shen, Yexiao He, Guoheng Sun, Hongyi Wang, Lingjuan Lyu, Ang Li
2024	A*	`conf`	Fusing Models with Complementary Expertise. ICLR Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin
2024	A*	`conf`	Maestro: Uncovering Low-Rank Structures via Trainable Decomposition. ICML Samuel Horváth, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang
2024	A*	`conf`	Model-GLUE: Democratized LLM Scaling for A Large Model Zoo in the Wild. NeurIPS Xinyu Zhao, Guoheng Sun, Ruisi Cai, Yukun Zhou, Pingzhi Li, Peihao Wang, Bowen Tan, Yexiao He, Li Chen, Yi Liang, Beidi Chen, Binhang Yuan, Hongyi Wang, Ang Li, Zhangyang Wang, Tianlong Chen
2024	J	`jnl`	Model-GLUE: Democratized LLM Scaling for A Large Model Zoo in the Wild. CoRR Xinyu Zhao, Guoheng Sun, Ruisi Cai, Yukun Zhou, Pingzhi Li, Peihao Wang, Bowen Tan, Yexiao He, Li Chen, Yi Liang, Beidi Chen, Binhang Yuan, Hongyi Wang, Ang Li, Zhangyang Wang, Tianlong Chen
2024	A*	`conf`	Position: TrustLLM: Trustworthiness in Large Language Models. ICML Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao
2024	J	`jnl`	Quantifying AI Psychology: A Psychometrics Benchmark for Large Language Models. CoRR Yuan Li, Yue Huang, Hongyi Wang, Xiangliang Zhang, James Zou, Lichao Sun
2024	—	`conf`	RedCoast: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs. NAACL (Demonstrations) Bowen Tan, Yun Zhu, Lijuan Liu, Hongyi Wang, Yonghao Zhuang, Jindong Chen, Eric P. Xing, Zhiting Hu
2024	A*	`conf`	SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning. NeurIPS Yexiao He, Ziyao Wang, Zheyu Shen, Guoheng Sun, Yucong Dai, Yongkai Wu, Hongyi Wang, Ang Li
2024	J	`jnl`	SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning. CoRR Yexiao He, Ziyao Wang, Zheyu Shen, Guoheng Sun, Yucong Dai, Yongkai Wu, Hongyi Wang, Ang Li
2024	J	`jnl`	TrustLLM: Trustworthiness in Large Language Models. CoRR Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao
2024	J	`jnl`	ViT-1.58b: Mobile Vision Transformers in the 1-bit Era. CoRR Zhengqing Yuan, Rong Zhou, Hongyi Wang, Lifang He, Yanfang Ye, Lichao Sun
2023	—	`conf`	Cuttlefish: Low-Rank Model Training without All the Tuning. MLSys Hongyi Wang, Saurabh Agarwal, Pongsakorn U.-Chupala, Yoshiki Tanaka, Eric P. Xing, Dimitris Papailiopoulos
2023	J	`jnl`	Cuttlefish: Low-Rank Model Training without All the Tuning. CoRR Hongyi Wang, Saurabh Agarwal, Pongsakorn U.-Chupala, Yoshiki Tanaka, Eric P. Xing, Dimitris S. Papailiopoulos
2023	J	`jnl`	Does compressing activations help model parallel training? CoRR Song Bian, Dacheng Li, Hongyi Wang, Eric P. Xing, Shivaram Venkataraman
2023	A*	`conf`	FedNAR: Federated Optimization with Normalized Annealing Regularization. NeurIPS Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang
2023	J	`jnl`	FedNAR: Federated Optimization with Normalized Annealing Regularization. CoRR Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang
2023	A*	`conf`	Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. ICLR Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing
2023	J	`jnl`	Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. CoRR Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing
2023	J	`jnl`	Fusing Models with Complementary Expertise. CoRR Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin
2023	J	`jnl`	LLM360: Towards Fully Transparent Open-Source LLMs. CoRR Zhengzhong Liu, Aurick Qiao, Willie Neiswanger, Hongyi Wang, Bowen Tan, Tianhua Tao, Junbo Li, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Yonghao Zhuang, Guowei He, Haonan Li, Fajri Koto, Liping Tang, Nikhil Ranjan, Zhiqiang Shen, Xuguang Ren, Roberto Iriondo, Cun Mu, Zhiting Hu, Mark Schulze, Preslav Nakov, Tim Baldwin, Eric P. Xing
2023	A*	`conf`	MPCFORMER: Fast, Performant and Provate Transformer Inference with MPC. ICLR Dacheng Li, Hongyi Wang, Rulin Shao, Han Guo, Eric P. Xing, Hao Zhang
2023	J	`jnl`	Maestro: Uncovering Low-Rank Structures via Trainable Decomposition. CoRR Samuel Horváth, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang
2023	J	`jnl`	Memory-adaptive Depth-wise Heterogenous Federated Learning. CoRR Kai Zhang, Yutong Dai, Hongyi Wang, Eric P. Xing, Xun Chen, Lichao Sun
2023	J	`jnl`	PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices. CoRR Minghao Yan, Hongyi Wang, Shivaram Venkataraman
2023	J	`jnl`	Redco: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs. CoRR Bowen Tan, Yun Zhu, Lijuan Liu, Hongyi Wang, Yonghao Zhuang, Jindong Chen, Eric P. Xing, Zhiting Hu
2023	J	`jnl`	SlimPajama-DC: Understanding Data Combinations for LLM Training. CoRR Zhiqiang Shen, Tianhua Tao, Liqun Ma, Willie Neiswanger, Zhengzhong Liu, Hongyi Wang, Bowen Tan, Joel Hestness, Natalia Vassilieva, Daria Soboleva, Eric P. Xing
2022	A*	`conf`	AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness. NeurIPS Dacheng Li, Hongyi Wang, Eric P. Xing, Hao Zhang
2022	J	`jnl`	AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness. CoRR Dacheng Li, Hongyi Wang, Eric P. Xing, Hao Zhang
2022	—	`conf`	Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation. EMNLP (Findings) Kai Zhang, Yu Wang, Hongyi Wang, Lifu Huang, Carl Yang, Xun Chen, Lichao Sun
2022	J	`jnl`	Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation. CoRR Kai Zhang, Yu Wang, Hongyi Wang, Lifu Huang, Carl Yang, Lichao Sun
2022	J	`jnl`	MPCFormer: fast, performant and private Transformer inference with MPC. CoRR Dacheng Li, Rulin Shao, Hongyi Wang, Han Guo, Eric P. Xing, Hao Zhang
2022	—	`conf`	On the Utility of Gradient Compression in Distributed Training Systems. MLSys Saurabh Agarwal, Hongyi Wang, Shivaram Venkataraman, Dimitris S. Papailiopoulos
2022	A*	`conf`	Rare Gems: Finding Lottery Tickets at Initialization. NeurIPS Kartik Sreenivasan, Jy-yong Sohn, Liu Yang, Matthew Grinde, Alliot Nagle, Hongyi Wang, Eric P. Xing, Kangwook Lee, Dimitris S. Papailiopoulos
2022	J	`jnl`	Rare Gems: Finding Lottery Tickets at Initialization. CoRR Kartik Sreenivasan, Jy-yong Sohn, Liu Yang, Matthew Grinde, Alliot Nagle, Hongyi Wang, Kangwook Lee, Dimitris S. Papailiopoulos
2021	J	`jnl`	A Field Guide to Federated Optimization. CoRR Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
2021	—	`conf`	Adaptive Gradient Communication via Critical Learning Regime Identification. MLSys Saurabh Agarwal, Hongyi Wang, Kangwook Lee, Shivaram Venkataraman, Dimitris S. Papailiopoulos
2021	J	`jnl`	On the Utility of Gradient Compression in Distributed Training Systems. CoRR Saurabh Agarwal, Hongyi Wang, Shivaram Venkataraman, Dimitris S. Papailiopoulos
2021	—	`conf`	Pufferfish: Communication-efficient Models At No Extra Cost. MLSys Hongyi Wang, Saurabh Agarwal, Dimitris S. Papailiopoulos
2021	J	`jnl`	Pufferfish: Communication-efficient Models At No Extra Cost. CoRR Hongyi Wang, Saurabh Agarwal, Dimitris S. Papailiopoulos
2021	J	`jnl`	Solon: Communication-efficient Byzantine-resilient Distributed Training via Redundant Gradients. CoRR Lingjiao Chen, Leshang Chen, Hongyi Wang, Susan B. Davidson, Edgar Dobriban
2020	J	`jnl`	Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification. CoRR Saurabh Agarwal, Hongyi Wang, Kangwook Lee, Shivaram Venkataraman, Dimitris S. Papailiopoulos
2020	A*	`conf`	Attack of the Tails: Yes, You Really Can Backdoor Federated Learning. NeurIPS Hongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal, Jy-yong Sohn, Kangwook Lee, Dimitris S. Papailiopoulos
2020	J	`jnl`	Attack of the Tails: Yes, You Really Can Backdoor Federated Learning. CoRR Hongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal, Jy-yong Sohn, Kangwook Lee, Dimitris S. Papailiopoulos
2020	J	`jnl`	FedML: A Research Library and Benchmark for Federated Machine Learning. CoRR Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram, Salman Avestimehr
2020	A*	`conf`	Federated Learning with Matched Averaging. ICLR Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris S. Papailiopoulos, Yasaman Khazaeni
2020	J	`jnl`	Federated Learning with Matched Averaging. CoRR Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris S. Papailiopoulos, Yasaman Khazaeni
2019	A*	`conf`	DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation. NeurIPS Shashank Rajput, Hongyi Wang, Zachary Charles, Dimitris S. Papailiopoulos
2019	J	`jnl`	DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation. CoRR Shashank Rajput, Hongyi Wang, Zachary Charles, Dimitris S. Papailiopoulos
2019	—	`conf`	Demonstration of Nimbus: Model-based Pricing for Machine Learning in a Data Marketplace. SIGMOD Conference Lingjiao Chen, Hongyi Wang, Leshang Chen, Paraschos Koutris, Arun Kumar
2019	J	`jnl`	ErasureHead: Distributed Gradient Descent without Delays Using Approximate Gradient Coding. CoRR Hongyi Wang, Zachary Charles, Dimitris S. Papailiopoulos
2018	A*	`conf`	ATOMO: Communication-efficient Learning via Atomic Sparsification. NeurIPS Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris S. Papailiopoulos, Stephen J. Wright
2018	J	`jnl`	ATOMO: Communication-efficient Learning via Atomic Sparsification. CoRR Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris S. Papailiopoulos, Stephen J. Wright
2018	A*	`conf`	DRACO: Byzantine-resilient Distributed Training via Redundant Gradients. ICML Lingjiao Chen, Hongyi Wang, Zachary Charles, Dimitris S. Papailiopoulos
2018	J	`jnl`	DRACO: Robust Distributed Training via Redundant Gradients. CoRR Lingjiao Chen, Hongyi Wang, Zachary Charles, Dimitris S. Papailiopoulos
2018	A*	`conf`	The Effect of Network Width on the Performance of Large-batch Training. NeurIPS Lingjiao Chen, Hongyi Wang, Jinman Zhao, Dimitris S. Papailiopoulos, Paraschos Koutris
2018	J	`jnl`	The Effect of Network Width on the Performance of Large-batch Training. CoRR Lingjiao Chen, Hongyi Wang, Jinman Zhao, Dimitris S. Papailiopoulos, Paraschos Koutris
2017	A	`conf`	Recognizing actions during tactile manipulations through force sensing. IROS Guru Subramani, Daniel Rakita, Hongyi Wang, Jordan Black, Michael R. Zinn, Michael Gleicher