Criticism towards traditional distributional models and the benchmarks used to evaluate them (Batchkarov et al., 2016) are now compelling more researchers to consider evaluation techniques that analyse how well distributional models encode different aspects of grounded meaning (Lucy and Gauthier, 2017;Collell and Moens, 2016;Gladkova and Drozd, 2016).
one aspect of cognitive plausibility that is lacking in dense representations is in their interpretability, something that could be solved using sparsity (Faruqui et al., 2015;Senel et al., 2017).