Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: What shapes feature representations? Exploring datasets, architectures,
  and training   In naturalistic learning problems, a model's input contains a wide range of
features, some useful for the task at hand, and others not. Of the useful
features, which ones does the model use? Of the task-irrelevant features, which
ones does the model represent? Answers to these questions are important for
understanding the basis of models' decisions, as well as for building models
that learn versatile, adaptable representations useful beyond the original
training task. We study these questions using synthetic datasets in which the
task-relevance of input features can be controlled directly. We find that when
two features redundantly predict the labels, the model preferentially
represents one, and its preference reflects what was most linearly decodable
from the untrained model. Over training, task-relevant features are enhanced,
and task-irrelevant features are partially suppressed. Interestingly, in some
cases, an easier, weakly predictive feature can suppress a more strongly
predictive, but more difficult one. Additionally, models trained to recognize
both easy and hard features learn representations most similar to models that
use only the easy feature. Further, easy features lead to more consistent
representations across model runs than do hard features. Finally, models have
greater representational similarity to an untrained model than to models
trained on a different task. Our results highlight the complex processes that
determine which features a model represents.

14
The categories of this paper are: math-ph
10
The categories of this paper are: q-bio
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
20
The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
29
The categories of this paper are: funct-an
37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
8
The categories of this paper are: hep-ex
23
The categories of this paper are: solv-int
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex
2
The categories of this paper are: math