Indeed, when evaluating these VSMs with datasets such as wordsim353 (Finkelstein et al., 2001), where the word pair scores re-flect association rather than similarity (and therefore the (cup,coffee) pair is scored higher than the (car,train) pair), the Spearman correlation between their scores and the human scores often crosses the 0.7 level.
when evaluating with datasets such as SimLex999 (Hill et al., 2014), where the pair scores reflect similarity, the correlation of these models with human judgment is below 0.5 (Section 6).