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Found 4 papers, 2 papers with code
Unlearning with Fisher Masking
Experiments on various datasets and network structures show the effectiveness of the method: without any fine-tuning, the proposed Fisher masking could unlearn almost completely while maintaining most of the performance on the remain data.
Few Clean Instances Help Denoising Distant Supervision
Existing distantly supervised relation extractors usually rely on noisy data for both model training and evaluation, which may lead to garbage-in-garbage-out systems.
Generating CCG Categories
Previous CCG supertaggers usually predict categories using multi-class classification.
AntNLP at CoNLL 2018 Shared Task: A Graph-Based Parser for Universal Dependency Parsing
We describe the graph-based dependency parser in our system (AntNLP) submitted to the CoNLL 2018 UD Shared Task.
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