Story Cloze Ending Selection Baselines and Data Examination
Table 2: Comparison of our models to shared task participants’ results and other baselines. Word2Vec sim, Skip-thoughts sim and DSSM are described in [Mostafazadeh et al.2016b].
['[BOLD] System', '[BOLD] Accuracy']
Overall results. Our features baseline system is our best feature-based system using embeddings and word2vec trained on Dev and tuned with cross-validation. The best result in the task is achieved by \newciteSchwartz2017-story-cloze (msap) who employ stylistic features combined with RNN representations. We have no information about cogcomp and ukp.