Chen, Yiming

17 publications

ICML 2025 A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models Yiming Chen, Yuan Zhang, Yin Liu, Kun Yuan, Zaiwen Wen

ICCV 2025 Clink! Chop! Thud! - Learning Object Sounds from Real-World Interactions Mengyu Yang, Yiming Chen, Haozheng Pei, Siddhant Agarwal, Arun Balajee Vasudevan, James Hays

ICLR 2025 Enhancing Zeroth-Order Fine-Tuning for Language Models with Low-Rank Structures Yiming Chen, Yuan Zhang, Liyuan Cao, Kun Yuan, Zaiwen Wen

ICCV 2025 FDPT: Federated Discrete Prompt Tuning for Black-Box Visual-Language Models Jiaqi Wu, Simin Chen, Jing Tang, Yuzhe Yang, Yiming Chen, Lixu Wang, Song Lin, Zehua Wang, Wei Chen, Zijian Tian

NeurIPS 2025 HARDMath2: A Benchmark for Applied Mathematics Built by Students as Part of a Graduate Class James V Roggeveen, Erik Y. Wang, David Ettel, Will Flintoft, Peter Donets, Raglan Ward, Ahmed Roman, Anton Marius Graf, Siddharth Dandavate, Ava Williamson, Felix Yeung, Kacper K Migacz, Yijun Wang, Egemen Bostan, Duy Thuc Nguyen, Zhe He, Marc L. Descoteaux, Anne Mykland, Shida Liu, Jorge García Ponce, Luke Zhu, Yuyang Chen, Ekaterina S. Ivshina, Miguel Fernandez, Minjae Kim, Kennan Gumbs, Matthew Scott Tan, Russell Yang, Mai Hoang, David Brown, Isabella A Silveira, Lavon Sykes, Arjun Nageswaran, William Fredenberg, Yiming Chen, Lucas Martin, Yixing Tang, Kelly Werker Smith, Hongyu Liao, Logan G. Wilson, Alexander Dazhen Cai, Lucy S. Nathwani, Nickholas Gutierrez, Andrea Elizabeth Biju, Michael Brenner

NeurIPS 2025 OmniTry: Virtual Try-on Anything Without Masks Yutong Feng, Linlin Zhang, Hengyuan Cao, Yiming Chen, Xiaoduan Feng, Jian Cao, Yuxiong Wu, Bin Wang

AAAI 2024 A Comprehensive Analysis of the Effectiveness of Large Language Models as Automatic Dialogue Evaluators Chen Zhang, Luis Fernando D'Haro, Yiming Chen, Malu Zhang, Haizhou Li

NeurIPS 2024 DreamMesh4D: Video-to-4D Generation with Sparse-Controlled Gaussian-Mesh Hybrid Representation Zhiqi Li, Yiming Chen, Peidong Liu

AAAI 2024 Progressive Poisoned Data Isolation for Training-Time Backdoor Defense Yiming Chen, Haiwei Wu, Jiantao Zhou

ECCV 2024 Unveiling Privacy Risks in Stochastic Neural Networks Training: Effective Image Reconstruction from Gradients Yiming Chen, Xiangyu Yang, Nikos Deligiannis

CVPR 2023 Effective Ambiguity Attack Against Passport-Based DNN Intellectual Property Protection Schemes Through Fully Connected Layer Substitution Yiming Chen, Jinyu Tian, Xiangyu Chen, Jiantao Zhou

NeurIPS 2022 Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan

NeurIPS 2022 Revisiting Optimal Convergence Rate for Smooth and Non-Convex Stochastic Decentralized Optimization Kun Yuan, Xinmeng Huang, Yiming Chen, Xiaohan Zhang, Yingya Zhang, Pan Pan

ICML 2021 Accelerating Gossip SGD with Periodic Global Averaging Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin

ICCV 2021 Bias Loss for Mobile Neural Networks Lusine Abrahamyan, Valentin Ziatchin, Yiming Chen, Nikos Deligiannis

ICCV 2021 DecentLaM: Decentralized Momentum SGD for Large-Batch Deep Training Kun Yuan, Yiming Chen, Xinmeng Huang, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin

NeurIPS 2021 Exponential Graph Is Provably Efficient for Decentralized Deep Training Bicheng Ying, Kun Yuan, Yiming Chen, Hanbin Hu, Pan Pan, Wotao Yin