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knowledge distillation

4,137 papers

KD

Papers

Distilling Knowledge From Graph Convolutional Networks CVPR 2020 Distilling Knowledge from Well-Informed Soft Labels for Neural Relation Extraction AAAI 2020 Distilling Knowledge Learned in BERT for Text Generation ACL 2020 Distilling Multiple Domains for Neural Machine Translation EMNLP 2020 Distilling Neural Networks for Greener and Faster Dependency Parsing ACL 2020 Distilling Portable Generative Adversarial Networks for Image Translation AAAI 2020 Distilling Structured Knowledge for Text-Based Relational Reasoning EMNLP 2020 Distilling the Knowledge of BERT for Sequence-to-Sequence ASR Interspeech 2020 Distributed Distillation for On-Device Learning NeurIPS 2020 Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks ICML 2020 Does label smoothing mitigate label noise? ICML 2020 Dreaming to Distill: Data-Free Knowledge Transfer via DeepInversion CVPR 2020 Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks ICML 2020 Dual Policy Distillation IJCAI 2020 DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles NeurIPS 2020 DynaBERT: Dynamic BERT with Adaptive Width and Depth NeurIPS 2020 Efficient and High-Quality Neural Machine Translation with OpenNMT ACL 2020 Efficient Meta Lifelong-Learning with Limited Memory EMNLP 2020 Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning EMNLP 2020 EigenEmo: Spectral Utterance Representation Using Dynamic Mode Decomposition for Speech Emotion Classification Interspeech 2020 End-to-End Speech-Translation with Knowledge Distillation: FBK@IWSLT2020 ACL 2020 ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation ACL 2020 Ensemble Approaches for Uncertainty in Spoken Language Assessment Interspeech 2020 Ensemble Distillation for Robust Model Fusion in Federated Learning NeurIPS 2020 Ensemble Distillation for Structured Prediction: Calibrated, Accurate, Fast—Choose Three EMNLP 2020