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Found 4 papers, 4 papers with code
Correlations between Word Vector Sets
Just like cosine similarity is used to compare individual word vectors, we introduce a novel application of the centered kernel alignment (CKA) as a natural generalisation of squared cosine similarity for sets of word vectors.
Correlation Coefficients and Semantic Textual Similarity
Importantly, we show that Pearson correlation is appropriate for some word vectors but not others.
Don't Settle for Average, Go for the Max: Fuzzy Sets and Max-Pooled Word Vectors
Recent literature suggests that averaged word vectors followed by simple post-processing outperform many deep learning methods on semantic textual similarity tasks.
Decoding Decoders: Finding Optimal Representation Spaces for Unsupervised Similarity Tasks
Experimental evidence indicates that simple models outperform complex deep networks on many unsupervised similarity tasks.
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