Wang, Hongyi

28 publications

AAAI 2025 M2OST: Many-to-One Regression for Predicting Spatial Transcriptomics from Digital Pathology Images Hongyi Wang, Xiuju Du, Jing Liu, Shuyi Ouyang, Yen-Wei Chen, Lanfen Lin

ICLRW 2025 MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression Tianyu Fu, Haofeng Huang, Xuefei Ning, Genghan Zhang, Boju Chen, Tianqi Wu, Hongyi Wang, Zixiao Huang, Shiyao Li, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang

ICCV 2025 Region-Aware Anchoring Mechanism for Efficient Referring Visual Grounding Shuyi Ouyang, Ziwei Niu, Hongyi Wang, Yen-Wei Chen, Lanfen Lin

NeurIPS 2024 $\texttt{Model-GLUE}$: 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, Hongyi Wang, Ang Li, Zhangyang Wang, Tianlong Chen

NeurIPSW 2024 A Large-Scale Foundation Model for RNA Function and Structure Prediction Shuxian Zou, Tianhua Tao, Sazan Mahbub, Caleb Ellington, Robin Jonathan Algayres, Dian Li, Yonghao Zhuang, Hongyi Wang, Le Song, Eric P. Xing

NeurIPSW 2024 Accurate and General DNA Representations Emerge from Genome Foundation Models at Scale Caleb Ellington, Ning Sun, Nicholas Ho, Tianhua Tao, Sazan Mahbub, Dian Li, Yonghao Zhuang, Hongyi Wang, Eric P. Xing, Le Song

NeurIPSW 2024 CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing Wenhao Zheng, Yixiao Chen, Weitong Zhang, Souvik Kundu, Yun Li, Zhengzhong Liu, Eric P. Xing, Hongyi Wang, Huaxiu Yao

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

ICLR 2024 Fusing Models with Complementary Expertise Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric Xing, Mikhail Yurochkin

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

NeurIPSW 2024 Mixture of Experts Enable Efficient and Effective Protein Understanding and Design Ning Sun, Shuxian Zou, Tianhua Tao, Sazan Mahbub, Dian Li, Yonghao Zhuang, Hongyi Wang, Xingyi Cheng, Le Song, Eric P. Xing

ICML 2024 Position: TrustLLM: Trustworthiness in Large Language Models 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 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 Yang Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao

NeurIPS 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, Ang Li

NeurIPSW 2024 Scaling Dense Representations for Single Cell Gene Expression with Transcriptome-Scale Context Nicholas Ho, Caleb Ellington, Jinyu Hou, Sohan Addagudi, Shentong Mo, Tianhua Tao, Dian Li, Yonghao Zhuang, Hongyi Wang, Xingyi Cheng, Le Song, Eric P. Xing

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

ICLR 2023 Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric Xing

NeurIPSW 2023 Fusing Models with Complementary Expertise Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin

NeurIPSW 2023 Maestro: Uncovering Low-Rank Structures via Trainable Decomposition Samuel Horváth, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang

ICLR 2023 Mpcformer: Fast, Performant and Private Transformer Inference with Mpc Dacheng Li, Hongyi Wang, Rulin Shao, Han Guo, Eric Xing, Hao Zhang

IJCAI 2023 SLViT: Scale-Wise Language-Guided Vision Transformer for Referring Image Segmentation Shuyi Ouyang, Hongyi Wang, Shiao Xie, Ziwei Niu, Ruofeng Tong, Yen-Wei Chen, Lanfen Lin

NeurIPS 2022 AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness Dacheng Li, Hongyi Wang, Eric P. Xing, Hao Zhang

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

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

ICLR 2020 Federated Learning with Matched Averaging Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris Papailiopoulos, Yasaman Khazaeni

NeurIPS 2019 DETOX: A Redundancy-Based Framework for Faster and More Robust Gradient Aggregation Shashank Rajput, Hongyi Wang, Zachary Charles, Dimitris Papailiopoulos

NeurIPS 2018 ATOMO: Communication-Efficient Learning via Atomic Sparsification Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris Papailiopoulos, Stephen Wright

ICML 2018 DRACO: Byzantine-Resilient Distributed Training via Redundant Gradients Lingjiao Chen, Hongyi Wang, Zachary Charles, Dimitris Papailiopoulos

NeurIPS 2018 The Effect of Network Width on the Performance of Large-Batch Training Lingjiao Chen, Hongyi Wang, Jinman Zhao, Dimitris Papailiopoulos, Paraschos Koutris