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Found 4 papers, 2 papers with code
Does She Wink or Does She Nod? A Challenging Benchmark for Evaluating Word Understanding of Language Models
Recent progress in pretraining language models on large corpora has resulted in significant performance gains on many NLP tasks.
Does He Wink or Does He Nod? A Challenging Benchmark for Evaluating Word Understanding of Language Models
Recent progress in pretraining language models on large corpora has resulted in large performance gains on many NLP tasks.
Imparting Interpretability to Word Embeddings while Preserving Semantic Structure
In other words, we align words that are already determined to be related, along predefined concepts.
Semantic Structure and Interpretability of Word Embeddings
Dense word embeddings, which encode semantic meanings of words to low dimensional vector spaces have become very popular in natural language processing (NLP) research due to their state-of-the-art performances in many NLP tasks.
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