Papers by Xiaoyong Jin

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Challenge:	Pretrained models have been taking the lead of many natural language processing benchmarks such as GLUE, but energy efficiency in the process of model training and inference becomes a critical bottleneck.
Approach:	They propose a multi-task energy efficiency benchmarking platform for responsible natural language processing that compares pretrained models’ energy efficiency from the perspectives of time and cost.
Outcome:	The proposed model improves on the fine-tuning efficiency of pretrained models from the perspectives of time and cost.