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Model Compression

1674 directly classified papers

Papers per year

Papers

AdapterHub: A Framework for Adapting Transformers EMNLP 2020
High Performance Natural Language Processing EMNLP 2020
Pruning Redundant Mappings in Transformer Models via Spectral-Normalized Identity Prior EMNLP 2020
Training Flexible Depth Model by Multi-Task Learning for Neural Machine Translation EMNLP 2020
Compressing Transformer-Based Semantic Parsing Models using Compositional Code Embeddings EMNLP 2020
Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation EMNLP 2020
Tensorized Embedding Layers EMNLP 2020
Dissecting Lottery Ticket Transformers: Structural and Behavioral Study of Sparse Neural Machine Translation EMNLP 2020
Rank and run-time aware compression of NLP Applications EMNLP 2020
End to End Binarized Neural Networks for Text Classification EMNLP 2020
Exploring the Boundaries of Low-Resource BERT Distillation EMNLP 2020
Overview of the SustaiNLP 2020 Shared Task EMNLP 2020
Dual Super-Resolution Learning for Semantic Segmentation CVPR 2020
FastBERT: a Self-distilling BERT with Adaptive Inference Time ACL 2020
Deep Implicit Volume Compression CVPR 2020
Resolution Adaptive Networks for Efficient Inference CVPR 2020
Rethinking Differentiable Search for Mixed-Precision Neural Networks CVPR 2020
DMCP: Differentiable Markov Channel Pruning for Neural Networks CVPR 2020
Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio AAAI 2020
Up or Down? Adaptive Rounding for Post-Training Quantization ICML 2020
T-Basis: a Compact Representation for Neural Networks ICML 2020
HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks NIPS 2020
Collaborative Distillation for Ultra-Resolution Universal Style Transfer CVPR 2020
AdaBits: Neural Network Quantization With Adaptive Bit-Widths CVPR 2020
Towards Efficient Model Compression via Learned Global Ranking CVPR 2020