| Index | Papers | Our Slides | 
  
  
    
      | 0 | A survey on Interpreting Deep Learning Models | Eli Survey | 
    
      |  | Interpretable Machine Learning: Definitions,Methods, Applications | Arsh Survey | 
    
      | 1 | Explaining Explanations: Axiomatic Feature Interactions for Deep Networks | Arsh Survey | 
    
      | 2 | Shapley Value review | Arsh Survey | 
    
      |  | L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data | Bill Survey | 
    
      |  | Consistent Individualized Feature Attribution for Tree Ensembles | bill Survey | 
    
      |  | Summary for A value for n-person games | Pan Survey | 
    
      |  | L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data | Rishab Survey | 
    
      | 3 | Hierarchical Interpretations of Neural Network Predictions | Arsh Survey | 
    
      |  | Hierarchical Interpretations of Neural Network Predictions | Rishab Survey | 
    
      | 4 | Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs | Arsh Survey | 
    
      |  | Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs | Rishab Survey | 
    
      | 5 | Towards Hierarchical Importance Attribution: Explaining Compositional Semantics for Neural Sequence Models | Rishab Survey | 
    
      |  |  | Sanchit Survey | 
    
      |  | Generating Hierarchical Explanations on Text Classification via Feature Interaction Detection | Sanchit Survey | 
    
      | 6 | This Looks Like That: Deep Learning for Interpretable Image Recognition | Pan Survey | 
    
      | 7 | AllenNLP Interpret | Rishab Survey | 
    
      | 8 | DISCOVERY OF NATURAL LANGUAGE CONCEPTS IN INDIVIDUAL UNITS OF CNNs | Rishab Survey | 
    
      | 9 | How Does BERT Answer Questions? A Layer-Wise Analysis of Transformer Representations | Rishab Survey | 
    
      | 10 | Attention is not Explanation | Sanchit Survey | 
    
      |  |  | Pan Survey | 
    
      | 11 | Axiomatic Attribution for Deep Networks | Sanchit Survey | 
    
      | 12 | Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization | Sanchit Survey | 
    
      | 13 | Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifier | Sanchit Survey | 
    
      | 14 | “Why Should I Trust You?”Explaining the Predictions of Any Classifier | Yu Survey | 
    
      | 15 | INTERPRETATIONS ARE USEFUL: PENALIZING EXPLANATIONS TO ALIGN NEURAL NETWORKS WITH PRIOR KNOWLEDGE | Pan Survey |