Knowledge Distillation

Distilling Causal Effect of Data in Class-Incremental Learning CVPR 2021 Distilling Global and Local Logits With Densely Connected Relations ICCV 2021 Distilling Holistic Knowledge With Graph Neural Networks ICCV 2021 Distilling Image Classifiers in Object Detectors NeurIPS 2021 Distilling Knowledge for Empathy Detection EMNLP 2021 Distilling Knowledge via Knowledge Review CVPR 2021 Distilling Linguistic Context for Language Model Compression EMNLP 2021 Distilling Meta Knowledge on Heterogeneous Graph for Illicit Drug Trafficker Detection on Social Media NeurIPS 2021 Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation CoRL 2021 Distilling Object Detectors via Decoupled Features CVPR 2021 Distilling Object Detectors with Feature Richness NeurIPS 2021 Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces ICCV 2021 Distilling Relation Embeddings from Pretrained Language Models EMNLP 2021 Distilling the Knowledge of Large-scale Generative Models into Retrieval Models for Efficient Open-domain Conversation EMNLP 2021 Distilling Virtual Examples for Long-Tailed Recognition ICCV 2021 Diverse Knowledge Distillation for End-to-End Person Search AAAI 2021 Diversity Matters When Learning From Ensembles NeurIPS 2021 Does Knowledge Distillation Really Work? NeurIPS 2021 Drop Redundant, Shrink Irrelevant: Selective Knowledge Injection for Language Pretraining IJCAI 2021 Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data NeurIPS 2021 Dynamic Knowledge Distillation for Pre-trained Language Models EMNLP 2021 Effectiveness of Arbitrary Transfer Sets for Data-Free Knowledge Distillation WACV 2021 Efficient Action Recognition via Dynamic Knowledge Propagation ICCV 2021 EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation EMNLP 2021 Efficient Machine Translation with Model Pruning and Quantization EMNLP 2021