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Environment Diversification with Multi-head Neural Network for Invariant Learning
On this issue, a research direction, invariant learning, has been proposed to extract invariant features insensitive to the distributional changes.
Explainable and Sparse Representations of Academic Articles for Knowledge Exploration
Provided with the interpretable concepts and knowledge encoded in a pre-trained neural model, we investigate whether the tagged concepts can be applied to a broader class of applications.
Explaining Word Embeddings via Disentangled Representation
Disentangled representations have attracted increasing attention recently.
Word Relation Autoencoder for Unseen Hypernym Extraction Using Word Embeddings
Lexicon relation extraction given distributional representation of words is an important topic in NLP.
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