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Found 5 papers, 1 papers with code
Always Keep your Target in Mind: Studying Semantics and Improving Performance of Neural Lexical Substitution
Lexical substitution, i. e. generation of plausible words that can replace a particular target word in a given context, is an extremely powerful technology that can be used as a backbone of various NLP applications, including word sense induction and disambiguation, lexical relation extraction, data augmentation, etc.
Combining Neural Language Models for WordSense Induction
Word sense induction (WSI) is the problem of grouping occurrences of an ambiguous word according to the expressed sense of this word.
A Comparative Study of Lexical Substitution Approaches based on Neural Language Models
Lexical substitution in context is an extremely powerful technology that can be used as a backbone of various NLP applications, such as word sense induction, lexical relation extraction, data augmentation, etc.
Combining Lexical Substitutes in Neural Word Sense Induction
Word Sense Induction (WSI) is the task of grouping of occurrences of an ambiguous word according to their meaning.
Neural GRANNy at SemEval-2019 Task 2: A combined approach for better modeling of semantic relationships in semantic frame induction
We describe our solutions for semantic frame and role induction subtasks of SemEval 2019 Task 2.
