40 citations · 77 across the 7 of their papers we have counts for
7 papers
Models of human preference for learning reward functions
W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth +3
The utility of reinforcement learning is limited by the alignment of reward functions with the interests of human stakeholders. One promising method for alignment is to learn the r…
Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development
Aspen Hopkins, Serena Booth
Practitioners from diverse occupations and backgrounds are increasingly using machine learning (ML) methods. Nonetheless, studies on ML Practitioners typically draw populations fro…
The Irrationality of Neural Rationale Models
Yiming Zheng, Serena Booth, Julie Shah +1
Neural rationale models are popular for interpretable predictions of NLP tasks. In these, a selector extracts segments of the input text, called rationales, and passes these segmen…
Do Feature Attribution Methods Correctly Attribute Features?
Yilun Zhou, Serena Booth, Marco Tulio Ribeiro +1
Feature attribution methods are popular in interpretable machine learning. These methods compute the attribution of each input feature to represent its importance, but there is no…
RoCUS: Robot Controller Understanding via Sampling
Yilun Zhou, Serena Booth, Nadia Figueroa +1
As robots are deployed in complex situations, engineers and end users must develop a holistic understanding of their behaviors, capabilities, and limitations. Some behaviors are di…
Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example
Serena Booth, Yilun Zhou, Ankit Shah +1
Post-hoc explanation methods are gaining popularity for interpreting, understanding, and debugging neural networks. Most analyses using such methods explain decisions in response t…
Sampling Prediction-Matching Examples in Neural Networks: A Probabilistic Programming Approach
Serena Booth, Ankit Shah, Yilun Zhou +1
Though neural network models demonstrate impressive performance, we do not understand exactly how these black-box models make individual predictions. This drawback has led to subst…