To achieve this, we introduce a learnable method for inter-layer ensemble strategy in the internal classifier, it trains the model to fit the information from ...
LMIE-BERT: A Learnable Method for Inter-Layer Ensembles to ...
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Feb 11, 2024 · LMIE-BERT: A Learnable Method for Inter-Layer Ensembles to Accelerate Inference of BERT-Style Pre-trained Models. August 2023. August 2023.
cadeBERT: Accelerating inference of pre-trained language models via calibrated complete models cascade,” in Findings of the Association for Computational ...
Bibliographic details on LMIE-BERT: A Learnable Method for Inter-Layer Ensembles to Accelerate Inference of BERT-Style Pre-trained Models.
Article "LMIE-BERT: A Learnable Method for Inter-Layer Ensembles to Accelerate Inference of BERT-Style Pre-trained Models" Detailed information of the ...
LMIE-BERT: A Learnable Method for Inter-Layer Ensembles to Accelerate Inference of BERT-Style Pre-trained Models ... This work introduces a learnable method for ...
This work proposes a simple but effective method, DeeBERT, to accelerate BERT inference, which allows samples to exit earlier without passing through the ...
May 23, 2024 · LMIE-BERT: A Learnable Method for Inter-Layer Ensembles to Accelerate Inference of BERT-Style Pre-trained Models. Conference Paper. Aug 2023.
Apr 7, 2024 · Abstract. Early Exiting is one of the most popular methods to achieve efficient inference. Current early exiting methods adopt the.
Abstract. Dynamic early exiting has been proven to improve the inference speed of the pre-trained language model like BERT. However, all samples must go.
Missing: LMIE- Ensembles