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Found 4 papers, 4 papers with code
Unifying Token and Span Level Supervisions for Few-Shot Sequence Labeling
However, these methods are only trained at a single granularity (i. e., either token level or span level) and have some weaknesses of the corresponding granularity.
Controlling Class Layout for Deep Ordinal Classification via Constrained Proxies Learning
For deep ordinal classification, learning a well-structured feature space specific to ordinal classification is helpful to properly capture the ordinal nature among classes.
Learning to Classify Open Intent via Soft Labeling and Manifold Mixup
In our method, soft labeling is used to reshape the label distribution of the known intent samples, aiming at reducing model's overconfident on known intents.
A Symmetric Local Search Network for Emotion-Cause Pair Extraction
Each subnetwork is composed of a clause representation learner and a local pair searcher.
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