Jun 4, 2021 · In order to stress test VQA models, we benchmark them against human-adversarial examples. Human subjects interact with a state-of-the-art VQA ...

In order to stress test VQA models, we benchmark them against human-adversarial examples. Human subjects interact with a state-of-the-art VQA model, and for.

Jun 10, 2024 · In order to stress test VQA models, we benchmark them against human-adversarial examples. Human subjects interact with a state-of-the-art VQA ...

Adversarial VQA is a new VQA benchmark that is collected with Human-And-Model-in-the-Loop for evaluating the robustness of state-of-the-art VQA systems.

Nov 9, 2021 · In order to stress test VQA models, we benchmark them against human-adversarial examples. Human subjects interact with a state-of-the-art VQA ...

In this work we propose a way to generate adversarial samples for the task of Visual Question Answering(VQA) by guiding our adversarial sample generation using ...

The models will need to understand and reason with rare concepts to do well on AdVQA since. 50.9% of the answers in AdVQA val and test sets do not occur in ...

Mar 19, 2023 · The widely used Fact-based Visual Question Answering (FVQA) dataset contains visually-grounded questions that require information retrieval using common sense ...

Missing: Visual | Show results with:Visual

Adversarial regularization (AdvReg) aims to address this issue via an adversary sub- network that encourages the main model to learn a bias-free representation ...