Papers by Annabelle Carrell
Attribute Diversity Determines the Systematicity Gap in VQA (2024.emnlp-main)
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| Challenge: | a systematicity gap exists between neural networks generalizing to new combinations of familiar concepts . conventionally trained neural networks struggle to generalize systematically . |
| Approach: | They propose to train a visual question answering model with CLEVR-HOPE as a diagnostic dataset to test this hypothesis. |
| Outcome: | The systematicity gap is reduced by increasing the diversity of training data, the authors show . the authors suggest that the more distinct attribute type combinations are seen during training, the more systematic the model will be. |