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Found 4 papers, 3 papers with code
Meta-Learning with Variational Semantic Memory for Word Sense Disambiguation
A critical challenge faced by supervised word sense disambiguation (WSD) is the lack of large annotated datasets with sufficient coverage of words in their diversity of senses.
A Multimodal Framework for the Detection of Hateful Memes
An increasingly common expression of online hate speech is multimodal in nature and comes in the form of memes.
Meta-Learning with Sparse Experience Replay for Lifelong Language Learning
Lifelong learning requires models that can continuously learn from sequential streams of data without suffering catastrophic forgetting due to shifts in data distributions.
Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation
Meta-learning aims to solve this problem by training a model on a large number of few-shot tasks, with an objective to learn new tasks quickly from a small number of examples.
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