2 citations · 2 across the 3 of their papers we have counts for
3 papers
Measuring Distributional Shifts in Text: The Advantage of Language Model-Based Embeddings
Gyandev Gupta, Bashir Rastegarpanah, Amalendu Iyer +2
An essential part of monitoring machine learning models in production is measuring input and output data drift. In this paper, we present a system for measuring distributional shif…
Visual Auditor: Interactive Visualization for Detection and Summarization of Model Biases
David Munechika, Zijie J. Wang, Jack Reidy +4
As machine learning (ML) systems become increasingly widespread, it is necessary to audit these systems for biases prior to their deployment. Recent research has developed algorith…
Unified Shapley Framework to Explain Prediction Drift
Aalok Shanbhag, Avijit Ghosh, Josh Rubin
Predictions are the currency of a machine learning model, and to understand the model's behavior over segments of a dataset, or over time, is an important problem in machine learni…