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SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
Haoming Jiang
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Pengcheng He
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Weizhu Chen
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Xiaodong Liu
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Jianfeng Gao
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Tuo Zhao
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Paper Details:
Month: July
Year: 2020
Location: Online
Venue:
ACL |
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https://github.com/namisan/mt-dnn
https://github.com/huggingface/transformers
https://github.com/pytorch/fairseq
https://github.com/namisan/mt-dnn
https://github.com/namisan/mt-dnn/tree/master/hnn
https://gluebenchmark.com/leaderboard
https://github.com/namisan/mt-dnn
Field Of Study
Linguistic Trends
Embeddings
Task
Language Understanding
Textual Entailment
Information Retrieval
Question Answering
Paraphrasing
Approach
Deep Learning
Semi-supervised Learning
Unsupervised Learning
Language
Multilingual