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Efficient Computing

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Papers

Certified Robustness to Programmable Transformations in LSTMs EMNLP 2021
Sparse Attention with Linear Units EMNLP 2021
MATE: Multi-view Attention for Table Transformer Efficiency EMNLP 2021
When Attention Meets Fast Recurrence: Training Language Models with Reduced Compute EMNLP 2021
Efficient Inference for Multilingual Neural Machine Translation EMNLP 2021
Sparsity and Sentence Structure in Encoder-Decoder Attention of Summarization Systems EMNLP 2021
Value-aware Approximate Attention EMNLP 2021
HypMix: Hyperbolic Interpolative Data Augmentation EMNLP 2021
FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging EMNLP 2021
How to Train BERT with an Academic Budget EMNLP 2021
Softmax Tree: An Accurate, Fast Classifier When the Number of Classes Is Large EMNLP 2021
TranslateLocally: Blazing-fast translation running on the local CPU EMNLP 2021
CascadeBERT: Accelerating Inference of Pre-trained Language Models via Calibrated Complete Models Cascade EMNLP 2021
Efficient Test Time Adapter Ensembling for Low-resource Language Varieties EMNLP 2021
BERT might be Overkill: A Tiny but Effective Biomedical Entity Linker based on Residual Convolutional Neural Networks EMNLP 2021
Language Resource Efficient Learning for Captioning EMNLP 2021
ARCH: Efficient Adversarial Regularized Training with Caching EMNLP 2021
Bag of Tricks for Optimizing Transformer Efficiency EMNLP 2021
Efficient Explanations from Empirical Explainers EMNLP 2021
Evaluating the carbon footprint of NLP methods: a survey and analysis of existing tools EMNLP 2021
Memory-efficient Transformers via Top-k Attention EMNLP 2021
Speeding Up Transformer Training By Using Dataset Subsampling - An Exploratory Analysis EMNLP 2021
Hyperparameter Power Impact in Transformer Language Model Training EMNLP 2021
Findings of the WMT 2021 Shared Task on Efficient Translation EMNLP 2021
Efficient Machine Translation with Model Pruning and Quantization EMNLP 2021