Recognizing actions during tactile manipulations through force sensing. - Guru Subramani; Daniel Rakita; Hongyi Wang 001; Jordan Black; Michael R. Zinn; Michael Gleicher (IROS, 2017)

DRACO: Byzantine-resilient Distributed Training via Redundant Gradients. - Lingjiao Chen; Hongyi Wang 001; Zachary Charles; Dimitris S. Papailiopoulos (ICML, 2018)

The Effect of Network Width on the Performance of Large-batch Training. - Lingjiao Chen; Hongyi Wang 001; Jinman Zhao; Dimitris S. Papailiopoulos; Paraschos Koutris (NeurIPS, 2018)

ATOMO: Communication-efficient Learning via Atomic Sparsification. - Hongyi Wang 001; Scott Sievert; Shengchao Liu; Zachary Charles; Dimitris S. Papailiopoulos; Stephen J. Wright 001 (NeurIPS, 2018)

DRACO: Robust Distributed Training via Redundant Gradients. - Lingjiao Chen; Hongyi Wang 001; Zachary Charles; Dimitris S. Papailiopoulos (CoRR, 2018)

DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation. - Shashank Rajput; Hongyi Wang 001; Zachary Charles; Dimitris S. Papailiopoulos (NeurIPS, 2019)

Demonstration of Nimbus: Model-based Pricing for Machine Learning in a Data Marketplace. - Lingjiao Chen; Hongyi Wang 001; Leshang Chen; Paraschos Koutris; Arun Kumar 001 (SIGMOD Conference, 2019)

ErasureHead: Distributed Gradient Descent without Delays Using Approximate Gradient Coding. - Hongyi Wang 001; Zachary Charles; Dimitris S. Papailiopoulos (CoRR, 2019)

Federated Learning with Matched Averaging. - Hongyi Wang 001; Mikhail Yurochkin; Yuekai Sun; Dimitris S. Papailiopoulos; Yasaman Khazaeni (ICLR, 2020)

Attack of the Tails: Yes, You Really Can Backdoor Federated Learning. - Hongyi Wang 001; Kartik Sreenivasan; Shashank Rajput; Harit Vishwakarma; Saurabh Agarwal; Jy-yong Sohn; Kangwook Lee 001; Dimitris S. Papailiopoulos (NeurIPS, 2020)

FedML: A Research Library and Benchmark for Federated Machine Learning. - Chaoyang He 001; Songze Li; Jinhyun So; Mi Zhang 002; Hongyi Wang 001; Xiaoyang Wang; Praneeth Vepakomma; Abhishek Singh 005; Hang Qiu 001; Li Shen 005; Peilin Zhao; Yan Kang 001; et al. (CoRR, 2020)

Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification. - Saurabh Agarwal; Hongyi Wang 001; Kangwook Lee 001; Shivaram Venkataraman; Dimitris S. Papailiopoulos (CoRR, 2020)

Adaptive Gradient Communication via Critical Learning Regime Identification. - Saurabh Agarwal; Hongyi Wang 001; Kangwook Lee 001; Shivaram Venkataraman; Dimitris S. Papailiopoulos (MLSys, 2021)

Pufferfish: Communication-efficient Models At No Extra Cost. - Hongyi Wang 001; Saurabh Agarwal; Dimitris S. Papailiopoulos (MLSys, 2021)

A Field Guide to Federated Optimization. - Jianyu Wang; Zachary Charles; Zheng Xu 002; Gauri Joshi; H. Brendan McMahan; Blaise Agüera y Arcas; Maruan Al-Shedivat; Galen Andrew; Salman Avestimehr; Katharine Daly; Deepesh Data; Suhas N. Diggavi; et al. (CoRR, 2021)

Solon: Communication-efficient Byzantine-resilient Distributed Training via Redundant Gradients. - Lingjiao Chen; Leshang Chen; Hongyi Wang 001; Susan B. Davidson; Edgar Dobriban (CoRR, 2021)

Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation. - Kai Zhang 039; Yu Wang 158; Hongyi Wang 001; Lifu Huang; Carl Yang 001; Xun Chen; Lichao Sun 001 (EMNLP (Findings), 2022)

On the Utility of Gradient Compression in Distributed Training Systems. - Saurabh Agarwal; Hongyi Wang 001; Shivaram Venkataraman; Dimitris S. Papailiopoulos (MLSys, 2022)

AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness. - Dacheng Li; Hongyi Wang 001; Eric P. Xing; Hao Zhang 025 (NeurIPS, 2022)

Rare Gems: Finding Lottery Tickets at Initialization. - Kartik Sreenivasan; Jy-yong Sohn; Liu Yang 001; Matthew Grinde; Alliot Nagle; Hongyi Wang 001; Eric P. Xing; Kangwook Lee 001; Dimitris S. Papailiopoulos (NeurIPS, 2022)

Rare Gems: Finding Lottery Tickets at Initialization. - Kartik Sreenivasan; Jy-yong Sohn; Liu Yang 001; Matthew Grinde; Alliot Nagle; Hongyi Wang 001; Kangwook Lee 001; Dimitris S. Papailiopoulos (CoRR, 2022)

Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation. - Kai Zhang 039; Yu Wang 158; Hongyi Wang 001; Lifu Huang; Carl Yang 001; Lichao Sun 001 (CoRR, 2022)

MPCFormer: fast, performant and private Transformer inference with MPC. - Dacheng Li; Rulin Shao; Hongyi Wang 001; Han Guo; Eric P. Xing; Hao Zhang 025 (CoRR, 2022)

Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. - Han Guo; Philip Greengard; Hongyi Wang 001; Andrew Gelman; Yoon Kim; Eric P. Xing (ICLR, 2023)

MPCFORMER: Fast, Performant and Provate Transformer Inference with MPC. - Dacheng Li; Hongyi Wang 001; Rulin Shao; Han Guo; Eric P. Xing; Hao Zhang 025 (ICLR, 2023)

Cuttlefish: Low-Rank Model Training without All the Tuning. - Hongyi Wang 001; Saurabh Agarwal; Pongsakorn U.-Chupala; Yoshiki Tanaka; Eric P. Xing; Dimitris Papailiopoulos (MLSys, 2023)

FedNAR: Federated Optimization with Normalized Annealing Regularization. - Junbo Li; Ang Li 005; Chong Tian; Qirong Ho; Eric P. Xing; Hongyi Wang 001 (NeurIPS, 2023)

Memory-adaptive Depth-wise Heterogenous Federated Learning. - Kai Zhang 039; Yutong Dai 002; Hongyi Wang 001; Eric P. Xing; Xun Chen; Lichao Sun 001 (CoRR, 2023)

SlimPajama-DC: Understanding Data Combinations for LLM Training. - Zhiqiang Shen; Tianhua Tao; Liqun Ma; Willie Neiswanger; Zhengzhong Liu 001; Hongyi Wang 001; Bowen Tan; Joel Hestness; Natalia Vassilieva; Daria Soboleva; Eric P. Xing (CoRR, 2023)

Redco: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs. - Bowen Tan; Yun Zhu; Lijuan Liu; Hongyi Wang 001; Yonghao Zhuang 001; Jindong Chen; Eric P. Xing; Zhiting Hu (CoRR, 2023)

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices. - Minghao Yan; Hongyi Wang 001; Shivaram Venkataraman (CoRR, 2023)

LLM360: Towards Fully Transparent Open-Source LLMs. - Zhengzhong Liu 001; Aurick Qiao; Willie Neiswanger; Hongyi Wang 001; Bowen Tan; Tianhua Tao; Junbo Li; Yuqi Wang; Suqi Sun; Omkar Pangarkar; Richard Fan; Yi Gu 002; et al. (CoRR, 2023)

Fusing Models with Complementary Expertise. - Hongyi Wang 001; Felipe Maia Polo; Yuekai Sun; Souvik Kundu 009; Eric P. Xing; Mikhail Yurochkin (ICLR, 2024)

Maestro: Uncovering Low-Rank Structures via Trainable Decomposition. - Samuel Horváth; Stefanos Laskaridis; Shashank Rajput; Hongyi Wang 001 (ICML, 2024)

Position: TrustLLM: Trustworthiness in Large Language Models. - Yue Huang; Lichao Sun 001; Haoran Wang 005; Siyuan Wu 001; Qihui Zhang; Yuan Li; Chujie Gao; Yixin Huang; Wenhan Lyu; Yixuan Zhang; Xiner Li; Hanchi Sun; et al. (ICML, 2024)

Does Compressing Activations Help Model Parallel Training? - Song Bian 002; Dacheng Li; Hongyi Wang 001; Eric P. Xing; Shivaram Venkataraman (MLSys, 2024)

RedCoast: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs. - Bowen Tan; Yun Zhu; Lijuan Liu; Hongyi Wang 001; Yonghao Zhuang 001; Jindong Chen; Eric P. Xing; Zhiting Hu (NAACL (Demonstrations), 2024)

SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning. - Yexiao He; Ziyao Wang; Zheyu Shen; Guoheng Sun; Yucong Dai; Yongkai Wu; Hongyi Wang 001; Ang Li 005 (NeurIPS, 2024)

FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations. - Ziyao Wang; Zheyu Shen; Yexiao He; Guoheng Sun; Hongyi Wang 001; Lingjuan Lyu; Ang Li 005 (NeurIPS, 2024)

Model-GLUE: Democratized LLM Scaling for A Large Model Zoo in the Wild. - Xinyu Zhao; Guoheng Sun; Ruisi Cai; Yukun Zhou; Pingzhi Li; Peihao Wang; Bowen Tan; Yexiao He; Li Chen; Yi Liang; Beidi Chen; Binhang Yuan; et al. (NeurIPS, 2024)

TrustLLM: Trustworthiness in Large Language Models. - Lichao Sun 001; Yue Huang 001; Haoran Wang 005; Siyuan Wu 001; Qihui Zhang; Chujie Gao; Yixin Huang; Wenhan Lyu; Yixuan Zhang 001; Xiner Li; Zhengliang Liu; Yixin Liu 002; et al. (CoRR, 2024)

Quantifying AI Psychology: A Psychometrics Benchmark for Large Language Models. - Yuan Li 032; Yue Huang 001; Hongyi Wang 001; Xiangliang Zhang 001; James Zou 001; Lichao Sun 001 (CoRR, 2024)

ViT-1.58b: Mobile Vision Transformers in the 1-bit Era. - Zhengqing Yuan; Rong Zhou; Hongyi Wang 001; Lifang He 001; Yanfang Ye 001; Lichao Sun 001 (CoRR, 2024)

Crystal: Illuminating LLM Abilities on Language and Code. - Tianhua Tao; Junbo Li; Bowen Tan; Hongyi Wang 001; William Marshall; Bhargav Kanakiya; Joel Hestness; Natalia Vassilieva; Zhiqiang Shen; Eric P. Xing; Zhengzhong Liu 001 (CoRR, 2024)

LLM360 K2: Building a 65B 360-Open-Source Large Language Model from Scratch. - Zhengzhong Liu 001; Bowen Tan; Hongyi Wang 001; Willie Neiswanger; Tianhua Tao; Haonan Li 002; Fajri Koto; Yuqi Wang; Suqi Sun; Omkar Pangarkar; Richard Fan; Yi Gu 002; et al. (CoRR, 2025)

CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing. - Wenhao Zheng; Yixiao Chen; Weitong Zhang; Souvik Kundu 009; Yun Li; Zhengzhong Liu 001; Eric P. Xing; Hongyi Wang 001; Huaxiu Yao (CoRR, 2025)

Token Level Routing Inference System for Edge Devices. - Jianshu She; Wenhao Zheng; Zhengzhong Liu 001; Hongyi Wang 001; Eric P. Xing; Huaxiu Yao; Qirong Ho (CoRR, 2025)