Others, staying closer to the surface level, have recently experimented with sophisticated measures of textual similarity (Jimenez et al., 2013;Sultan et al., 2016) or inferring informative answer patterns (Ramachandran et al., 2015).
similar to other NLP tasks (like, for example, TE), one of the biggest challenges remains beating the lexical baseline: At SemEval-2013, the baseline consisting of textual similarity measures comparing reference and student answer frequently was not outperformed.