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Shangqian Gao

34 papers · 2019–2026 · 12 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (44) πŸƒ Academic Marathon (6) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (12) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (12) πŸ† Keyword Champion (5) 🀝 Dynamic Duo (24) πŸ”¬ Deep Specialist (10) πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (110) ⚑ Prolific Year (9) πŸ’Ž Century Club (33) πŸ”₯ Unstoppable (7)

Conferences

CVPR (8) ICLR (4) AAAI (3) ECCV (3) EMNLP (3) ICCV (3) NIPS (3) JMLR (2) NAACL (2) ICML (1) IJCAI (1) WACV (1)

Top co-authors

Heng Huang (24) Feihu Huang (10) Yanfu Zhang (9) Yilin Shen (7) Hongxia Jin (7) Yen-Chang Hsu (6) Alireza Ganjdanesh (5) Cheng Deng (4) Zeyu Zhang (3) Chi-Heng Lin (3)

Keywords

model compression (13) convolutional neural network (5) channel pruning (5) large language model (4) structural pruning (3) model pruning (3) network pruning (3) data memorization (2) parameter efficiency (2) weight sharing (2) stochastic gradient (2) variance reduction (2) neural network pruning (2) knowledge distillation (2) efficient computing (2) singular value decomposition (2) zeroth-order optimization (2) low-rank approximation (2) manifold learning (1) nonconvex optimization (1)

Papers

Query-Efficient Domain Knowledge Stealing Against Large Language Models AAAI 2026
Controllable Memorization in LLMs via Weight Pruning EMNLP 2025
FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing NAACL 2025
Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models ICLR 2025
MoDeGPT: Modular Decomposition for Large Language Model Compression ICLR 2025
Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models CVPR 2025
BilevelPruning: Unified Dynamic and Static Channel Pruning for Convolutional Neural Networks CVPR 2024
Unlocking Memorization in Large Language Models with Dynamic Soft Prompting EMNLP 2024
DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models NIPS 2024
Compressing Image-to-Image Translation GANs Using Local Density Structures on Their Learned Manifold AAAI 2024
Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch CVPR 2024
Device-Wise Federated Network Pruning CVPR 2024
Jointly Training and Pruning CNNs via Learnable Agent Guidance and Alignment CVPR 2024
Adaptive Rank Selections for Low-Rank Approximation of Language Models NAACL 2024
Token Fusion: Bridging the Gap Between Token Pruning and Token Merging WACV 2024
Structural Alignment for Network Pruning through Partial Regularization ICCV 2023
Dynamic Low-rank Estimation for Transformer-based Language Models EMNLP 2023
EffConv: Efficient Learning of Kernel Sizes for Convolution Layers of CNNs AAAI 2023
Learning to Jointly Share and Prune Weights for Grounding Based Vision and Language Models ICLR 2023
Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps ECCV 2022
Bregman Gradient Policy Optimization ICLR 2022
Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization JMLR 2022
Enhanced Bilevel Optimization via Bregman Distance NIPS 2022
Disentangled Differentiable Network Pruning ECCV 2022
Recover Fair Deep Classification Models via Altering Pre-trained Structure ECCV 2022
Exploration and Estimation for Model Compression ICCV 2021
Adversarial Attack on Deep Cross-Modal Hamming Retrieval ICCV 2021
Network Pruning via Performance Maximization CVPR 2021
Black-Box Reductions for Zeroth-Order Gradient Algorithms to Achieve Lower Query Complexity JMLR 2021
Discrete Model Compression With Resource Constraint for Deep Neural Networks CVPR 2020
Momentum-Based Policy Gradient Methods ICML 2020
Cross-Modal Learning with Adversarial Samples NIPS 2019
Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization IJCAI 2019
Cross Domain Model Compression by Structurally Weight Sharing CVPR 2019