24 citations · 63 across the 13 of their papers we have counts for
14 papers
Evergreen: Efficient Claim Verification for Semantic Aggregates
Alexander W. Lee, Benjamin Han, Shayak Sen +3
With recent semantic query processing engines, semantic aggregation has become a primitive operator, enabling the reduction of a relation into a natural language aggregate using an…
What Is Your Agent's GPA? A Framework for Evaluating Agent Goal-Plan-Action Alignment
Allison Sihan Jia, Daniel Huang, Nikhil Vytla +5
We introduce the Agent GPA (Goal-Plan-Action) framework, driven by the fundamental insight that critical agent failures emerge at the intersections of setting goals, devising plans…
Feature-Wise Bias Amplification
Klas Leino, Emily Black, Matt Fredrikson +2
We study the phenomenon of bias amplification in classifiers, wherein a machine learning model learns to predict classes with a greater disparity than the underlying ground truth.…
Correspondences between Privacy and Nondiscrimination: Why They Should Be Studied Together
Anupam Datta, Shayak Sen, Michael Carl Tschantz
Privacy and nondiscrimination are related but different. We make this observation precise in two ways. First, we show that both privacy and nondiscrimination have two versions, a c…
Supervising Feature Influence
Shayak Sen, Piotr Mardziel, Anupam Datta +1
Causal influence measures for machine learnt classifiers shed light on the reasons behind classification, and aid in identifying influential input features and revealing their bias…
Influence-Directed Explanations for Deep Convolutional Networks
Klas Leino, Shayak Sen, Anupam Datta +2
We study the problem of explaining a rich class of behavioral properties of deep neural networks. Distinctively, our influence-directed explanations approach this problem by peerin…