Video Recovery via Learning Variation and Consistency of Images. - Zhouyuan Huo; Shangqian Gao; Weidong Cai 001; Heng Huang (AAAI, 2017)

Discriminative Multi-instance Multitask Learning for 3D Action Recognition. - Yanhua Yang; Cheng Deng; Shangqian Gao; Wei Liu 005; Dapeng Tao; Xinbo Gao 001 (IEEE Trans. Multim., 2017)

Action Prediction From Videos via Memorizing Hard-to-Predict Samples. - Yu Kong 001; Shangqian Gao; Bin Sun 002; Yun Fu 001 (AAAI, 2018)

Cross Domain Model Compression by Structurally Weight Sharing. - Shangqian Gao; Cheng Deng; Heng Huang (CVPR, 2019)

Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization. - Feihu Huang 001; Shangqian Gao; Songcan Chen; Heng Huang (IJCAI, 2019)

Cross-Modal Learning with Adversarial Samples. - Chao Li 033; Shangqian Gao; Cheng Deng; De Xie; Wei Liu 005 (NeurIPS, 2019)

Nonconvex Zeroth-Order Stochastic ADMM Methods with Lower Function Query Complexity. - Feihu Huang 001; Shangqian Gao; Jian Pei 001; Heng Huang (CoRR, 2019)

Discrete Model Compression With Resource Constraint for Deep Neural Networks. - Shangqian Gao; Feihu Huang 001; Jian Pei 001; Heng Huang (CVPR, 2020)

Momentum-Based Policy Gradient Methods. - Feihu Huang 001; Shangqian Gao; Jian Pei 001; Heng Huang (ICML, 2020)

Accelerated Zeroth-Order Momentum Methods from Mini to Minimax Optimization. - Feihu Huang 001; Shangqian Gao; Jian Pei 001; Heng Huang (CoRR, 2020)

Gradient Descent Ascent for Min-Max Problems on Riemannian Manifold. - Feihu Huang 001; Shangqian Gao; Heng Huang (CoRR, 2020)

Network Pruning via Performance Maximization. - Shangqian Gao; Feihu Huang 001; Weidong Cai 001; Heng Huang (CVPR, 2021)

Adversarial Attack on Deep Cross-Modal Hamming Retrieval. - Chao Li 033; Shangqian Gao; Cheng Deng; Wei Liu 005; Heng Huang (ICCV, 2021)

Exploration and Estimation for Model Compression. - Yanfu Zhang; Shangqian Gao; Heng Huang (ICCV, 2021)

Black-Box Reductions for Zeroth-Order Gradient Algorithms to Achieve Lower Query Complexity. - Bin Gu 001; Xiyuan Wei; Shangqian Gao; Ziran Xiong; Cheng Deng; Heng Huang (J. Mach. Learn. Res., 2021)

Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps. - Alireza Ganjdanesh; Shangqian Gao; Heng Huang (ECCV (21), 2022)

Disentangled Differentiable Network Pruning. - Shangqian Gao; Feihu Huang 001; Yanfu Zhang; Heng Huang (ECCV (11), 2022)

Recover Fair Deep Classification Models via Altering Pre-trained Structure. - Yanfu Zhang; Shangqian Gao; Heng Huang (ECCV (13), 2022)

Bregman Gradient Policy Optimization. - Feihu Huang 001; Shangqian Gao; Heng Huang (ICLR, 2022)

Improving Social Network Embedding via New Second-Order Continuous Graph Neural Networks. - Yanfu Zhang; Shangqian Gao; Jian Pei 001; Heng Huang (KDD, 2022)

Enhanced Bilevel Optimization via Bregman Distance. - Feihu Huang 001; Junyi Li; Shangqian Gao; Heng Huang (NeurIPS, 2022)

Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization. - Feihu Huang 001; Shangqian Gao; Jian Pei 001; Heng Huang (J. Mach. Learn. Res., 2022)

Riemannian gradient methods for stochastic composition problems. - Feihu Huang 001; Shangqian Gao (Neural Networks, 2022)

EffConv: Efficient Learning of Kernel Sizes for Convolution Layers of CNNs. - Alireza Ganjdanesh; Shangqian Gao; Heng Huang (AAAI, 2023)

Dynamic Low-rank Estimation for Transformer-based Language Models. - Ting Hua; Xiao Li; Shangqian Gao; Yen-Chang Hsu; Yilin Shen; Hongxia Jin (EMNLP (Findings), 2023)

Structural Alignment for Network Pruning through Partial Regularization. - Shangqian Gao; Zeyu Zhang; Yanfu Zhang; Feihu Huang 001; Heng Huang (ICCV, 2023)

Learning to Jointly Share and Prune Weights for Grounding Based Vision and Language Models. - Shangqian Gao; Burak Uzkent; Yilin Shen; Heng Huang; Hongxia Jin (ICLR, 2023)

Gradient Descent Ascent for Minimax Problems on Riemannian Manifolds. - Feihu Huang 001; Shangqian Gao (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Compressing Image-to-Image Translation GANs Using Local Density Structures on Their Learned Manifold. - Alireza Ganjdanesh; Shangqian Gao; Hirad Alipanah; Heng Huang (AAAI, 2024)

Jointly Training and Pruning CNNs via Learnable Agent Guidance and Alignment. - Alireza Ganjdanesh; Shangqian Gao; Heng Huang (CVPR, 2024)

Device-Wise Federated Network Pruning. - Shangqian Gao; Junyi Li; Zeyu Zhang; Yanfu Zhang; Weidong Cai 001; Heng Huang (CVPR, 2024)

BilevelPruning: Unified Dynamic and Static Channel Pruning for Convolutional Neural Networks. - Shangqian Gao; Yanfu Zhang; Feihu Huang 001; Heng Huang (CVPR, 2024)

Auto- Train-Once: Controller Network Guided Automatic Network Pruning from Scratch. - Xidong Wu; Shangqian Gao; Zeyu Zhang; Zhenzhen Li; Runxue Bao; Yanfu Zhang; Xiaoqian Wang 001; Heng Huang (CVPR, 2024)

Unlocking Memorization in Large Language Models with Dynamic Soft Prompting. - Zhepeng Wang 001; Runxue Bao; Yawen Wu; Jackson Taylor; Cao Xiao; Feng Zheng; Weiwen Jiang; Shangqian Gao; Yanfu Zhang (EMNLP, 2024)

Adaptive Rank Selections for Low-Rank Approximation of Language Models. - Shangqian Gao; Ting Hua; Yen-Chang Hsu; Yilin Shen; Hongxia Jin (NAACL-HLT, 2024)

DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models. - Shangqian Gao; Chi-Heng Lin; Ting Hua; Zheng Tang; Yilin Shen; Hongxia Jin; Yen-Chang Hsu (NeurIPS, 2024)

Token Fusion: Bridging the Gap between Token Pruning and Token Merging. - Minchul Kim; Shangqian Gao; Yen-Chang Hsu; Yilin Shen; Hongxia Jin (WACV, 2024)

DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models. - Shangqian Gao; Chi-Heng Lin; Ting Hua; Tang Zheng; Yilin Shen; Hongxia Jin; Yen-Chang Hsu (CoRR, 2024)

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs. - Lei Lu; Zhepeng Wang 001; Runxue Bao; Mengbing Wang; Fangyi Li; Yawen Wu; Weiwen Jiang; Jie Xu; Yanzhi Wang; Shangqian Gao (CoRR, 2024)

Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models. - Reza Shirkavand; Peiran Yu; Shangqian Gao; Gowthami Somepalli; Tom Goldstein; Heng Huang (CVPR, 2025)

Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models. - Alireza Ganjdanesh; Reza Shirkavand; Shangqian Gao; Heng Huang (ICLR, 2025)

MoDeGPT: Modular Decomposition for Large Language Model Compression. - Chi-Heng Lin; Shangqian Gao; James Seale Smith; Abhishek Patel; Shikhar Tuli; Yilin Shen; Hongxia Jin; Yen-Chang Hsu (ICLR, 2025)

FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing. - James Seale Smith; Chi-Heng Lin; Shikhar Tuli; Haris Jeelani; Shangqian Gao; Yilin Shen; Hongxia Jin; Yen-Chang Hsu (NAACL (Long Papers), 2025)

ToMoE: Converting Dense Large Language Models to Mixture-of-Experts through Dynamic Structural Pruning. - 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; et al. (CoRR, 2025)

Dynamic Noise Preference Optimization for LLM Self-Improvement via Synthetic Data. - Haoyan Yang; Ting Hua; Shangqian Gao; Binfeng Xu; Zheng Tang; Jie Xu; Hongxia Jin; Vijay Srinivasan (CoRR, 2025)

Any Large Language Model Can Be a Reliable Judge: Debiasing with a Reasoning-based Bias Detector. - Haoyan Yang; Runxue Bao; Cao Xiao; Jun Ma; Parminder Bhatia; Shangqian Gao; Taha A. Kass-Hout (CoRR, 2025)

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation. - Xiaomeng Yang; Lei Lu; Qihui Fan; Changdi Yang; Juyi Lin; Yanzhi Wang; Xuan Zhang; Shangqian Gao (CoRR, 2025)

TreeDiff: AST-Guided Code Generation with Diffusion LLMs. - Yiming Zeng 012; Jinghan Cao; Zexin Li; Yiming Chen; Tao Ren; Dawei Xiang; Xidong Wu; Shangqian Gao; Tingting Yu (CoRR, 2025)