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Found 6 papers, 1 papers with code
Relation Adversarial Network for Low Resource Knowledge Graph Completion
Specifically, the framework takes advantage of a relation discriminator to distinguish between samples from different relations, and help learn relation-invariant features more transferable from source relations to target relations.
Transfer Learning for Relation Extraction via Relation-Gated Adversarial Learning
However, the human annotation is expensive, while human-crafted patterns suffer from semantic drift and distant supervision samples are usually noisy.
When Low Resource NLP Meets Unsupervised Language Model: Meta-pretraining Then Meta-learning for Few-shot Text Classification
Text classification tends to be difficult when data are deficient or when it is required to adapt to unseen classes.
Ranked #1 on
Multi-Domain Sentiment Classification
on ARSC
Capturing Evolution Genes for Time Series Data
The modeling of time series is becoming increasingly critical in a wide variety of applications.
Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks
Here, the challenge is to learn accurate "few-shot" models for classes existing at the tail of the class distribution, for which little data is available.
Attention-Based Capsule Networks with Dynamic Routing for Relation Extraction
A capsule is a group of neurons, whose activity vector represents the instantiation parameters of a specific type of entity.
