model avg seen ± sd avg unseen ± sd CNN+LSTM 0.608 ± 0.01 0.4036 ± 0.003 CNN+LSTM+SA 0.7813 ± 0.009 0.235 ± 0.006 FiLM 0.8489 ± 0.014 0.153 ± 0.02 chance 0.5 0.5  We tackle the modeling of size GAs as a relational problem in the domain of visual reasoning, and show (in contrast with Kuhnle et al., 2018) that FiLM is able to learn the function underlying the meaning of these expressions.
none of the models develop an abstract representation of GAs that can be applied compositionally, an ability that even 4-year-olds master (Barner and Snedeker, 2008).