Characterizing the Efficiency vs. Accuracy Trade-off for Long-Context NLP Models

@article{Ang2022CharacterizingTE,
  title={Characterizing the Efficiency vs. Accuracy Trade-off for Long-Context NLP Models},
  author={Phyllis Ang and Bhuwan Dhingra and Lisa Wu Wills},
  journal={ArXiv},
  year={2022},
  volume={abs/2204.07288}
}
With many real-world applications of Natural Language Processing (NLP) comprising of long texts, there has been a rise in NLP benchmarks that measure the accuracy of models that can handle longer input sequences. However, these benchmarks do not consider the trade-offs between accuracy, speed, and power consumption as input sizes or model sizes are varied. In this work, we perform a systematic study of this accuracy vs. efficiency trade-off on two widely used long-sequence models - Longformer… 
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