Learning Probabilistic Sentence Representations from Paraphrases
Table 8: Pearson correlation (%) for STS benchmark test set. Highest number is in bold.
['[EMPTY]', 'STS Benchmark']
When using probabilistic models to predict sentence similarity during test time, we let v1=concat(μ1,Σ1), v2=concat(μ2,Σ2), where concat is a concatenation operation, and predict sentence similarity via cosine(v1,v2), since we find it performs better than solely using the mean vectors. The two probabilistic models, LSTMGaussian and WLO, are able to outperform the baselines slightly.