An Empirical Study on Adaptive Inference for Pretrained Language Model

Adaptive inference has been proven to improve bidirectional encoder representations from transformers (BERT)'s inference speed with minimal loss of accuracy. However, current work only focuses on the BERT model and lacks exploration of other pretrained language models (PLMs). Therefore, this ar...

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Vydané v:	IEEE transaction on neural networks and learning systems Ročník 34; číslo 8; s. 4321 - 4331
Hlavní autori:	Liu, Weijie, Zhao, Xin, Zhao, Zhe, Ju, Qi, Yang, Xuefeng, Lu, Wei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.08.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Acceleration Adaptation models Adaptive inference Benchmarks bidirectional encoder representations from transformers (BERT) Bit error rate Coders Computational modeling distillation FastPLM Inference Inference mechanisms Labels Language Mathematical models pretrained language model (PLM) Task analysis Transformers
ISSN:	2162-237X, 2162-2388, 2162-2388
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