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neural network compression

114 papers

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Co-occurring keywords

model compression (3283) neural network (6616) knowledge distillation (3680) model quantization (279) neural network pruning (265) neural network optimization (1293) model pruning (233) convolutional neural network (4216) transfer learning (5442) network pruning (183)

Papers

FQ-PETR: Fully Quantized Position Embedding Transformation for Multi-View 3D Object Detection AAAI 2026
FP=XINT: Representing Neural Networks via Low-Bit Series Basis Functions AAAI 2026
Aligning Sizes of Intermediate Layers by LoRA Adapter for Knowledge Distillation NAACL 2025
Self-Attentive Spatio-Temporal Calibration for Precise Intermediate Layer Matching in ANN-to-SNN Distillation AAAI 2025
APHQ-ViT: Post-Training Quantization with Average Perturbation Hessian Based Reconstruction for Vision Transformers CVPR 2025
Talking Head Anime 4: Distillation for Real-Time Performance WACV 2025
LaCoOT: Layer Collapse through Optimal Transport ICCV 2025
Automatic Joint Structured Pruning and Quantization for Efficient Neural Network Training and Compression CVPR 2025
Till the Layers Collapse: Compressing a Deep Neural Network Through the Lenses of Batch Normalization Layers. AAAI 2025
Enhancing Diversity for Data-free Quantization CVPR 2025
Robust Machine Unlearning for Quantized Neural Networks via Adaptive Gradient Reweighting with Similar Labels ICCV 2025
Training a Tucker Model With Shared Factors: a Riemannian Optimization Approach AISTATS 2024
Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training NIPS 2024
Geometry-aware training of factorized layers in tensor Tucker format NIPS 2024
One-pass Multiple Conformer and Foundation Speech Systems Compression and Quantization Using An All-in-one Neural Model INTERSPEECH 2024
Quantization of Large Language Models with an Overdetermined Basis UAI 2024
VeriCompress: A Tool to Streamline the Synthesis of Verified Robust Compressed Neural Networks from Scratch AAAI 2024
DSD²: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free? AAAI 2024
Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression JMLR 2024
One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training AAAI 2024
BMRS: Bayesian Model Reduction for Structured Pruning NIPS 2024
Comparing the Decision-Making Mechanisms by Transformers and CNNs via Explanation Methods CVPR 2024
Adaptive Data-Free Quantization CVPR 2023
UPSCALE: Unconstrained Channel Pruning ICML 2023
Joint Token Pruning and Squeezing Towards More Aggressive Compression of Vision Transformers CVPR 2023