Shangqian Gao - RankMe

71 papers A* 28A 1Journal 36Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Dynamic Bayesian Optimization Framework for Instruction Tuning in Partial Differential Equation Discovery. CoRR Junqi Qu, Yan Zhang, Shangqian Gao, Shibo Li
2026	J	`jnl`	GeoMotionGPT: Geometry-Aligned Motion Understanding with Large Language Models. CoRR Zhankai Ye, Bofan Li, Yukai Jin, Shuoqiu Li, Wei Wang, Yanfu Zhang, Shangqian Gao, Xin Liu
2026	A*	`conf`	Query-Efficient Domain Knowledge Stealing Against Large Language Models. AAAI Zhengao Li, Xiaopeng Yuan, Bolin Shen, Kien Le, Haohan Wang, Xugui Zhou, Shangqian Gao, Yushun Dong
2026	J	`jnl`	ToMoE: Converting Dense Large Language Models to Mixture-of-Experts through Dynamic Structural Pruning. Trans. Mach. Learn. Res. Shangqian Gao, Ting Hua, Reza Shirkavand, Chi-Heng Lin, Zheng Tang, Zhengao Li, Longge Yuan, Fangyi Li, Zeyu Zhang, Alireza Ganjdanesh, Qian Lou, Jie Xu, Yen-Chang Hsu
2026	J	`jnl`	Transform-Augmented GRPO Improves Pass@k. CoRR Khiem Le, Youssef Mroueh, Phuc Nguyen, Chi-Heng Lin, Shangqian Gao, Ting Hua, Nitesh V. Chawla
2025	J	`jnl`	ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation. CoRR Xiaomeng Yang, Lei Lu, Qihui Fan, Changdi Yang, Juyi Lin, Yanzhi Wang, Xuan Zhang, Shangqian Gao
2025	J	`jnl`	Any Large Language Model Can Be a Reliable Judge: Debiasing with a Reasoning-based Bias Detector. CoRR Haoyan Yang, Runxue Bao, Cao Xiao, Jun Ma, Parminder Bhatia, Shangqian Gao, Taha A. Kass-Hout
2025	A*	`conf`	Controllable Memorization in LLMs via Weight Pruning. EMNLP Chenjie Ni, Zhepeng Wang, Runxue Bao, Shangqian Gao, Yanfu Zhang
2025	J	`jnl`	Cost-Aware Contrastive Routing for LLMs. CoRR Reza Shirkavand, Shangqian Gao, Peiran Yu, Heng Huang
2025	J	`jnl`	DictPFL: Efficient and Private Federated Learning on Encrypted Gradients. CoRR Jiaqi Xue, Mayank Kumar, Yuzhang Shang, Shangqian Gao, Rui Ning, Mengxin Zheng, Xiaoqian Jiang, Qian Lou
2025	J	`jnl`	Dynamic Noise Preference Optimization for LLM Self-Improvement via Synthetic Data. CoRR Haoyan Yang, Ting Hua, Shangqian Gao, Binfeng Xu, Zheng Tang, Jie Xu, Hongxia Jin, Vijay Srinivasan
2025	A*	`conf`	Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models. CVPR Reza Shirkavand, Peiran Yu, Shangqian Gao, Gowthami Somepalli, Tom Goldstein, Heng Huang
2025	—	`conf`	FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing. NAACL (Long Papers) James Seale Smith, Chi-Heng Lin, Shikhar Tuli, Haris Jeelani, Shangqian Gao, Yilin Shen, Hongxia Jin, Yen-Chang Hsu
2025	J	`jnl`	FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing. CoRR James Seale Smith, Chi-Heng Lin, Shikhar Tuli, Haris Jeelani, Shangqian Gao, Yilin Shen, Hongxia Jin, Yen-Chang Hsu
2025	J	`jnl`	HyperEdit: Unlocking Instruction-based Text Editing in LLMs via Hypernetworks. CoRR Yiming Zeng, Jinghan Cao, Zexin Li, Wanhao Yu, Zhankai Ye, Dawei Xiang, Ting Hua, Xin Liu, Shangqian Gao, Tingting Yu
2025	A*	`conf`	MoDeGPT: Modular Decomposition for Large Language Model Compression. ICLR Chi-Heng Lin, Shangqian Gao, James Seale Smith, Abhishek Patel, Shikhar Tuli, Yilin Shen, Hongxia Jin, Yen-Chang Hsu
2025	A*	`conf`	Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models. ICLR Alireza Ganjdanesh, Reza Shirkavand, Shangqian Gao, Heng Huang
2025	J	`jnl`	PRO: Enabling Precise and Robust Text Watermark for Open-Source LLMs. CoRR Jiaqi Xue, Yifei Zhao, Mansour Al Ghanim, Shangqian Gao, Ruimin Sun, Qian Lou, Mengxin Zheng
2025	J	`jnl`	ToMoE: Converting Dense Large Language Models to Mixture-of-Experts through Dynamic Structural Pruning. CoRR Shangqian Gao, Ting Hua, Reza Shirkavand, Chi-Heng Lin, Zhen Tang, Zhengao Li, Longge Yuan, Fangyi Li, Zeyu Zhang, Alireza Ganjdanesh, Qian Lou, Xu Jie, Yen-Chang Hsu
2025	J	`jnl`	TreeDiff: AST-Guided Code Generation with Diffusion LLMs. CoRR Yiming Zeng, Jinghan Cao, Zexin Li, Yiming Chen, Tao Ren, Dawei Xiang, Xidong Wu, Shangqian Gao, Tingting Yu
2024	—	`conf`	Adaptive Rank Selections for Low-Rank Approximation of Language Models. NAACL-HLT Shangqian Gao, Ting Hua, Yen-Chang Hsu, Yilin Shen, Hongxia Jin
2024	J	`jnl`	All-in-One Tuning and Structural Pruning for Domain-Specific LLMs. CoRR Lei Lu, Zhepeng Wang, Runxue Bao, Mengbing Wang, Fangyi Li, Yawen Wu, Weiwen Jiang, Jie Xu, Yanzhi Wang, Shangqian Gao
2024	A*	`conf`	Auto- Train-Once: Controller Network Guided Automatic Network Pruning from Scratch. CVPR Xidong Wu, Shangqian Gao, Zeyu Zhang, Zhenzhen Li, Runxue Bao, Yanfu Zhang, Xiaoqian Wang, Heng Huang
2024	J	`jnl`	Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch. CoRR Xidong Wu, Shangqian Gao, Zeyu Zhang, Zhenzhen Li, Runxue Bao, Yanfu Zhang, Xiaoqian Wang, Heng Huang
2024	A*	`conf`	BilevelPruning: Unified Dynamic and Static Channel Pruning for Convolutional Neural Networks. CVPR Shangqian Gao, Yanfu Zhang, Feihu Huang, Heng Huang
2024	A*	`conf`	Compressing Image-to-Image Translation GANs Using Local Density Structures on Their Learned Manifold. AAAI Alireza Ganjdanesh, Shangqian Gao, Hirad Alipanah, Heng Huang
2024	A*	`conf`	DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models. NeurIPS Shangqian Gao, Chi-Heng Lin, Ting Hua, Zheng Tang, Yilin Shen, Hongxia Jin, Yen-Chang Hsu
2024	J	`jnl`	DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models. CoRR Shangqian Gao, Chi-Heng Lin, Ting Hua, Tang Zheng, Yilin Shen, Hongxia Jin, Yen-Chang Hsu
2024	A*	`conf`	Device-Wise Federated Network Pruning. CVPR Shangqian Gao, Junyi Li, Zeyu Zhang, Yanfu Zhang, Weidong Cai, Heng Huang
2024	J	`jnl`	Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models. CoRR Reza Shirkavand, Peiran Yu, Shangqian Gao, Gowthami Somepalli, Tom Goldstein, Heng Huang
2024	A*	`conf`	Jointly Training and Pruning CNNs via Learnable Agent Guidance and Alignment. CVPR Alireza Ganjdanesh, Shangqian Gao, Heng Huang
2024	J	`jnl`	Jointly Training and Pruning CNNs via Learnable Agent Guidance and Alignment. CoRR Alireza Ganjdanesh, Shangqian Gao, Heng Huang
2024	J	`jnl`	MoDeGPT: Modular Decomposition for Large Language Model Compression. CoRR Chi-Heng Lin, Shangqian Gao, James Seale Smith, Abhishek Patel, Shikhar Tuli, Yilin Shen, Hongxia Jin, Yen-Chang Hsu
2024	J	`jnl`	Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models. CoRR Alireza Ganjdanesh, Reza Shirkavand, Shangqian Gao, Heng Huang
2024	A	`conf`	Token Fusion: Bridging the Gap between Token Pruning and Token Merging. WACV Minchul Kim, Shangqian Gao, Yen-Chang Hsu, Yilin Shen, Hongxia Jin
2024	A*	`conf`	Unlocking Memorization in Large Language Models with Dynamic Soft Prompting. EMNLP Zhepeng Wang, Runxue Bao, Yawen Wu, Jackson Taylor, Cao Xiao, Feng Zheng, Weiwen Jiang, Shangqian Gao, Yanfu Zhang
2024	J	`jnl`	Unlocking Memorization in Large Language Models with Dynamic Soft Prompting. CoRR Zhepeng Wang, Runxue Bao, Yawen Wu, Jackson Taylor, Cao Xiao, Feng Zheng, Weiwen Jiang, Shangqian Gao, Yanfu Zhang
2023	J	`jnl`	Compressing Image-to-Image Translation GANs Using Local Density Structures on Their Learned Manifold. CoRR Alireza Ganjdanesh, Shangqian Gao, Hirad Alipanah, Heng Huang
2023	—	`conf`	Dynamic Low-rank Estimation for Transformer-based Language Models. EMNLP (Findings) Ting Hua, Xiao Li, Shangqian Gao, Yen-Chang Hsu, Yilin Shen, Hongxia Jin
2023	A*	`conf`	EffConv: Efficient Learning of Kernel Sizes for Convolution Layers of CNNs. AAAI Alireza Ganjdanesh, Shangqian Gao, Heng Huang
2023	J	`jnl`	Gradient Descent Ascent for Minimax Problems on Riemannian Manifolds. IEEE Trans. Pattern Anal. Mach. Intell. Feihu Huang, Shangqian Gao
2023	A*	`conf`	Learning to Jointly Share and Prune Weights for Grounding Based Vision and Language Models. ICLR Shangqian Gao, Burak Uzkent, Yilin Shen, Heng Huang, Hongxia Jin
2023	A*	`conf`	Structural Alignment for Network Pruning through Partial Regularization. ICCV Shangqian Gao, Zeyu Zhang, Yanfu Zhang, Feihu Huang, Heng Huang
2023	J	`jnl`	Token Fusion: Bridging the Gap between Token Pruning and Token Merging. CoRR Minchul Kim, Shangqian Gao, Yen-Chang Hsu, Yilin Shen, Hongxia Jin
2022	J	`jnl`	Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization. J. Mach. Learn. Res. Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
2022	A*	`conf`	Bregman Gradient Policy Optimization. ICLR Feihu Huang, Shangqian Gao, Heng Huang
2022	—	`conf`	Disentangled Differentiable Network Pruning. ECCV (11) Shangqian Gao, Feihu Huang, Yanfu Zhang, Heng Huang
2022	A*	`conf`	Enhanced Bilevel Optimization via Bregman Distance. NeurIPS Feihu Huang, Junyi Li, Shangqian Gao, Heng Huang
2022	A*	`conf`	Improving Social Network Embedding via New Second-Order Continuous Graph Neural Networks. KDD Yanfu Zhang, Shangqian Gao, Jian Pei, Heng Huang
2022	—	`conf`	Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps. ECCV (21) Alireza Ganjdanesh, Shangqian Gao, Heng Huang
2022	J	`jnl`	Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps. CoRR Alireza Ganjdanesh, Shangqian Gao, Heng Huang
2022	—	`conf`	Recover Fair Deep Classification Models via Altering Pre-trained Structure. ECCV (13) Yanfu Zhang, Shangqian Gao, Heng Huang
2022	J	`jnl`	Riemannian gradient methods for stochastic composition problems. Neural Networks Feihu Huang, Shangqian Gao
2021	A*	`conf`	Adversarial Attack on Deep Cross-Modal Hamming Retrieval. ICCV Chao Li, Shangqian Gao, Cheng Deng, Wei Liu, Heng Huang
2021	J	`jnl`	Black-Box Reductions for Zeroth-Order Gradient Algorithms to Achieve Lower Query Complexity. J. Mach. Learn. Res. Bin Gu, Xiyuan Wei, Shangqian Gao, Ziran Xiong, Cheng Deng, Heng Huang
2021	J	`jnl`	Bregman Gradient Policy Optimization. CoRR Feihu Huang, Shangqian Gao, Heng Huang
2021	A*	`conf`	Exploration and Estimation for Model Compression. ICCV Yanfu Zhang, Shangqian Gao, Heng Huang
2021	A*	`conf`	Network Pruning via Performance Maximization. CVPR Shangqian Gao, Feihu Huang, Weidong Cai, Heng Huang
2020	J	`jnl`	Accelerated Zeroth-Order Momentum Methods from Mini to Minimax Optimization. CoRR Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
2020	A*	`conf`	Discrete Model Compression With Resource Constraint for Deep Neural Networks. CVPR Shangqian Gao, Feihu Huang, Jian Pei, Heng Huang
2020	J	`jnl`	Gradient Descent Ascent for Min-Max Problems on Riemannian Manifold. CoRR Feihu Huang, Shangqian Gao, Heng Huang
2020	A*	`conf`	Momentum-Based Policy Gradient Methods. ICML Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
2020	J	`jnl`	Momentum-Based Policy Gradient Methods. CoRR Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
2019	A*	`conf`	Cross Domain Model Compression by Structurally Weight Sharing. CVPR Shangqian Gao, Cheng Deng, Heng Huang
2019	A*	`conf`	Cross-Modal Learning with Adversarial Samples. NeurIPS Chao Li, Shangqian Gao, Cheng Deng, De Xie, Wei Liu
2019	J	`jnl`	Nonconvex Zeroth-Order Stochastic ADMM Methods with Lower Function Query Complexity. CoRR Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
2019	A*	`conf`	Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization. IJCAI Feihu Huang, Shangqian Gao, Songcan Chen, Heng Huang
2019	J	`jnl`	Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization. CoRR Feihu Huang, Shangqian Gao, Songcan Chen, Heng Huang
2018	A*	`conf`	Action Prediction From Videos via Memorizing Hard-to-Predict Samples. AAAI Yu Kong, Shangqian Gao, Bin Sun, Yun Fu
2017	J	`jnl`	Discriminative Multi-instance Multitask Learning for 3D Action Recognition. IEEE Trans. Multim. Yanhua Yang, Cheng Deng, Shangqian Gao, Wei Liu, Dapeng Tao, Xinbo Gao
2017	A*	`conf`	Video Recovery via Learning Variation and Consistency of Images. AAAI Zhouyuan Huo, Shangqian Gao, Weidong Cai, Heng Huang