Model Compression

Too Brittle to Touch: Comparing the Stability of Quantization and Distillation towards Developing Low-Resource MT Models EMNLP 2022 Towards Efficient NLP: A Standard Evaluation and A Strong Baseline NAACL 2022 Towards Fair Dataset Distillation for Text Classification EMNLP 2022 Towards Light-Weight and Real-Time Line Segment Detection AAAI 2022 Tracking Down Misguiding Terms for Locating Bugs in Deep Learning-Based Software (Student Abstract) AAAI 2022 Training Your Sparse Neural Network Better with Any Mask ICML 2022 Tricks for Training Sparse Translation Models NAACL 2022 TSPipe: Learn from Teacher Faster with Pipelines ICML 2022 Tutoring Helps Students Learn Better: Improving Knowledge Distillation for BERT with Tutor Network EMNLP 2022 Wavelet Feature Maps Compression for Image-to-Image CNNs NeurIPS 2022 Weighted Mutual Learning with Diversity-Driven Model Compression NeurIPS 2022 What Do Compressed Multilingual Machine Translation Models Forget? EMNLP 2022 When To Prune? A Policy Towards Early Structural Pruning CVPR 2022 Winning the Lottery Ahead of Time: Efficient Early Network Pruning ICML 2022 YOLO-ReT: Towards High Accuracy Real-Time Object Detection on Edge GPUs WACV 2022 Zero-Shot Dynamic Quantization for Transformer Inference EMNLP 2022 ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization NeurIPS 2022 1-bit Adam: Communication Efficient Large-Scale Training with Adam’s Convergence Speed ICML 2021 Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework ICML 2021 Accelerating BERT Inference for Sequence Labeling via Early-Exit ACL 2021 Accelerating Neural Machine Translation with Partial Word Embedding Compression AAAI 2021 Accurate Post Training Quantization With Small Calibration Sets ICML 2021 Achieving On-Mobile Real-Time Super-Resolution With Neural Architecture and Pruning Search ICCV 2021 Against Membership Inference Attack: Pruning is All You Need IJCAI 2021 An Efficient Transformer Decoder with Compressed Sub-layers AAAI 2021