model compression

Tensor decomposition for minimization of E2E SLU model toward on-device processing Interspeech 2023 TexQ: Zero-shot Network Quantization with Texture Feature Distribution Calibration NeurIPS 2023 Text Representation Distillation via Information Bottleneck Principle EMNLP 2023 The Cost of Compression: Investigating the Impact of Compression on Parametric Knowledge in Language Models EMNLP 2023 The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter NeurIPS 2023 Three Guidelines You Should Know for Universally Slimmable Self-Supervised Learning CVPR 2023 TinyHD: Efficient Video Saliency Prediction With Heterogeneous Decoders Using Hierarchical Maps Distillation WACV 2023 TinyMIM: An Empirical Study of Distilling MIM Pre-Trained Models CVPR 2023 TinyNeRF: Towards 100 x Compression of Voxel Radiance Fields AAAI 2023 TIPS: Topologically Important Path Sampling for Anytime Neural Networks ICML 2023 Token-Scaled Logit Distillation for Ternary Weight Generative Language Models NeurIPS 2023 TORE: Token Reduction for Efficient Human Mesh Recovery with Transformer ICCV 2023 Toward Accurate Post-Training Quantization for Image Super Resolution CVPR 2023 Toward Large Kernel Models ICML 2023 Towards a Smaller Student: Capacity Dynamic Distillation for Efficient Image Retrieval CVPR 2023 Towards Efficient Pre-Trained Language Model via Feature Correlation Distillation NeurIPS 2023 Towards Fairness-aware Adversarial Network Pruning ICCV 2023 Towards Fully Quantized Neural Networks For Speech Enhancement Interspeech 2023 Towards Higher Ranks via Adversarial Weight Pruning NeurIPS 2023 Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting CVPR 2023 Towards Lossless Head Pruning through Automatic Peer Distillation for Language Models IJCAI 2023 Toward Stable, Interpretable, and Lightweight Hyperspectral Super-Resolution CVPR 2023 Towards Understanding and Improving Knowledge Distillation for Neural Machine Translation ACL 2023 Towards Understanding Ensemble Distillation in Federated Learning ICML 2023 Trainability Preserving Neural Pruning ICLR 2023