Papers with VQA models
Overcoming Language Priors in Visual Question Answering via Distinguishing Superficially Similar Instances (2022.coling-1)
Copied to clipboard
| Challenge: | Existing VQA models rely on the superficial correlation between question type and frequent answers to make predictions, without really understanding the input. |
| Approach: | They propose a training framework that explicitly encourages the VQA model to distinguish between superficially similar instances. |
| Outcome: | The proposed framework achieves state-of-the-art performance on VQA-CP v2 . it explicitly encourages the model to distinguish between the superficially similar instances . |