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Found 3 papers, 1 papers with code
Leveraging Domain Agnostic and Specific Knowledge for Acronym Disambiguation
In this paper, we consider both the domain agnostic and specific knowledge, and propose a Hierarchical Dual-path BERT method coined hdBERT to capture the general fine-grained and high-level specific representations for acronym disambiguation.
AT-BERT: Adversarial Training BERT for Acronym Identification Winning Solution for SDU@AAAI-21
In this paper, we present an Adversarial Training BERT method named AT-BERT, our winning solution to acronym identification task for Scientific Document Understanding (SDU) Challenge of AAAI 2021.
Continual Learning of Context-dependent Processing in Neural Networks
Deep neural networks (DNNs) are powerful tools in learning sophisticated but fixed mapping rules between inputs and outputs, thereby limiting their application in more complex and dynamic situations in which the mapping rules are not kept the same but changing according to different contexts.
Ranked #5 on
Continual Learning
on ASC (19 tasks)
