Learning Visually Grounded Sentence Representations
Table 2: Accuracy results on sentence classification and entailment tasks.
['[BOLD] Model', '[BOLD] MR', '[BOLD] CR', '[BOLD] SUBJ', '[BOLD] MPQA', '[BOLD] MRPC', '[BOLD] SST', '[BOLD] SNLI', '[BOLD] SICK']
Note that all systems use the exact same evaluation pipeline, which makes them directly comparable. We can see that in all cases, grounding increases the performance. The question of which type of grounding works best is more difficult: generally, grounding with Cap2Cap and Cap2Both appears to do slightly better on most tasks, but on e.g. SST, Cap2Img works better.