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Found 4 papers, 1 papers with code
Semi-supervised Relation Extraction via Data Augmentation and Consistency-training
Due to the semantic complexity of the Relation extraction (RE) task, obtaining high-quality human labelled data is an expensive and noisy process.
Inductive Relation Prediction by Subgraph Reasoning
The dominant paradigm for relation prediction in knowledge graphs involves learning and operating on latent representations (i. e., embeddings) of entities and relations.
Off-Policy Policy Gradient Algorithms by Constraining the State Distribution Shift
This data distribution shift between current and past samples can significantly impact the performance of most modern off-policy based policy optimization algorithms.
Towards Reducing Bias in Gender Classification
Societal bias towards certain communities is a big problem that affects a lot of machine learning systems.
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