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Encoder-only transformer models such as BERT offer a great performance-size tradeoff for retrieval and classification tasks with respect to larger decoder-only models.
Representation degeneration problem in training natural language generation models
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Roberta: A robustly optimized BERT pretraining approach
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Roberta: A robustly optimized BERT pretraining approach
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Codesearchnet challenge: Evaluating the state of semantic code search
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Megatron-lm: Training multi-billion parameter language models using model parallelism
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On the difficulty of warm-starting neural network training
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Glu variants improve transformer
Noam Shazeer. 2020 · 2002
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Longformer: The long-document transformer
Iz Beltagy, Matthew E. Peters, and Arman Cohan. 2020 · 2004
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Chen Xing, Devansh Arpit, Christos Tsirigotis, and Yoshua Bengio. 2018 · 2018
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Ilya Loshchilov and Frank Hutter. 2019 · 2019
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Jingjing Xu, Xu Sun, Zhiyuan Zhang, Guangxiang Zhao, and Junyang Lin. 2019 · 2019
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Language models are few-shot learners
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Hard negative examples are hard, but useful
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