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Found 3 papers, 1 papers with code
Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning
Recently, modular networks have been shown to be an effective framework for performing visual reasoning tasks.
Ranked #4 on
Visual Question Answering (VQA)
on CLEVR
Tools and Practices for Responsible AI Engineering
Responsible Artificial Intelligence (AI) - the practice of developing, evaluating, and maintaining accurate AI systems that also exhibit essential properties such as robustness and explainability - represents a multifaceted challenge that often stretches standard machine learning tooling, frameworks, and testing methods beyond their limits.
Fourier-Based Augmentations for Improved Robustness and Uncertainty Calibration
Diverse data augmentation strategies are a natural approach to improving robustness in computer vision models against unforeseen shifts in data distribution.
