Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: How clever is the FiLM model, and how clever can it be?   The FiLM model achieves close-to-perfect performance on the diagnostic CLEVR
dataset and is distinguished from other such models by having a comparatively
simple and easily transferable architecture. In this paper, we investigate in
more detail the ability of FiLM to learn various linguistic constructions. Our
main results show that (a) FiLM is not able to learn relational statements
straight away except for very simple instances, (b) training on a broader set
of instances as well as pretraining on simpler instance types can help
alleviate these learning difficulties, (c) mixing is less robust than
pretraining and very sensitive to the compositional structure of the dataset.
Overall, our results suggest that the approach of big all-encompassing datasets
and the paradigm of "the effectiveness of data" may have fundamental
limitations.

11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
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The categories of this paper are: solv-int
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The categories of this paper are: comp-gas
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The categories of this paper are: bayes-an
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The categories of this paper are: nlin
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol