research
∙
08/28/2023
Identifying and Mitigating the Security Risks of Generative AI
Every major technical invention resurfaces the dual-use dilemma – the ne...
share
research
∙
06/01/2022
Order-sensitive Shapley Values for Evaluating Conceptual Soundness of NLP Models
Previous works show that deep NLP models are not always conceptually sou...
research
∙
05/24/2022
Faithful Explanations for Deep Graph Models
This paper studies faithful explanations for Graph Neural Networks (GNNs...
research
∙
10/06/2021
Consistent Counterfactuals for Deep Models
Counterfactual examples are one of the most commonly-cited methods for e...
research
∙
03/20/2021
Boundary Attributions Provide Normal (Vector) Explanations
Recent work on explaining Deep Neural Networks (DNNs) focuses on attribu...
research
∙
11/02/2020
Abstracting Influence Paths for Explaining (Contextualization of) BERT Models
While "attention is all you need" may be proving true, we do not yet kno...
research
∙
09/17/2020
Towards Behavior-Level Explanation for Deep Reinforcement Learning
While Deep Neural Networks (DNNs) are becoming the state-of-the-art for ...
research
∙
06/14/2020
Fairness Under Feature Exemptions: Counterfactual and Observational Measures
With the growing use of AI in highly consequential domains, the quantifi...
research
∙
06/11/2020
Smoothed Geometry for Robust Attribution
Feature attributions are a popular tool for explaining the behavior of D...
research
∙
05/03/2020
Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models
LSTM-based recurrent neural networks are the state-of-the-art for many n...
research
∙
02/19/2020
Interpreting Interpretations: Organizing Attribution Methods by Criteria
Attribution methods that explains the behaviour of machine learning mode...
research
∙
12/21/2018
Feature-Wise Bias Amplification
We study the phenomenon of bias amplification in classifiers, wherein a ...
research
∙
10/16/2018
Hunting for Discriminatory Proxies in Linear Regression Models
A machine learning model may exhibit discrimination when used to make de...
research
∙
08/06/2018
Correspondences between Privacy and Nondiscrimination: Why They Should Be Studied Together
Privacy and nondiscrimination are related but different. We make this ob...
research
∙
07/31/2018
Gender Bias in Neural Natural Language Processing
We examine whether neural natural language processing (NLP) systems refl...
research
∙
03/28/2018
Supervising Feature Influence
Causal influence measures for machine learnt classifiers shed light on t...
research
∙
02/11/2018
Influence-Directed Explanations for Deep Convolutional Networks
We study the problem of explaining a rich class of behavioral properties...
research
∙
11/29/2017
Latent Factor Interpretations for Collaborative Filtering
Many machine learning systems utilize latent factors as internal represe...
research
∙
09/27/2017
