Explaining Model Decisions and Fixing Them Through Human Feedback

Explaining Model Decisions and Fixing Them Through Human Feedback

Stanford MedAI via YouTube Direct link

Interpretability in different stages of Al evolution

2 of 21

2 of 21

Interpretability in different stages of Al evolution

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Explaining Model Decisions and Fixing Them Through Human Feedback

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  1. 1 Intro
  2. 2 Interpretability in different stages of Al evolution
  3. 3 Approaches for visual explanations
  4. 4 Visualize any decision
  5. 5 Visualizing Image Captioning models
  6. 6 Visualizing Visual Question Answering models
  7. 7 Analyzing Failure modes
  8. 8 Grad-CAM for predicting patient outcomes
  9. 9 Extensions to Multi-modal Transformer based Architectures
  10. 10 Desirable properties of Visual Explanations
  11. 11 Equalizer
  12. 12 Biases in Vision and Language models
  13. 13 Human Importance-aware Network Tuning (HINT)
  14. 14 Contrastive Self-Supervised Learning (SSL)
  15. 15 Why SSL methods fail to generalize to arbitrary images?
  16. 16 Does improved SSL grounding transfer to downstream tasks?
  17. 17 CAST makes models resilient to background changes
  18. 18 VQA for visually impaired users
  19. 19 Sub-Question Importance-aware Network Tuning
  20. 20 Explaining Model Decisions and Fixing them via Human Feedback
  21. 21 Grad-CAM for multi-modal transformers

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