most citedFreaAI: Automated extraction of data slices to test machine learning models

26 citations · 27 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2022

Measuring the Measuring Tools: An Automatic Evaluation of Semantic Metrics for Text Corpora

George Kour, Samuel Ackerman, Orna Raz +3

The ability to compare the semantic similarity between text corpora is important in a variety of natural language processing applications. However, standard methods for evaluating…

cs.HC20221 cited

High-quality Conversational Systems

Samuel Ackerman, Ateret Anaby-Tavor, Eitan Farchi +7

Conversational systems or chatbots are an example of AI-Infused Applications (AIIA). Chatbots are especially important as they are often the first interaction of clients with a bus…

cs.LG2021

Density-based interpretable hypercube region partitioning for mixed numeric and categorical data

Samuel Ackerman, Eitan Farchi, Orna Raz +2

Consider a structured dataset of features, such as . A user may want to know where in the feature space obser…

cs.LG202126 cited

FreaAI: Automated extraction of data slices to test machine learning models

Samuel Ackerman, Orna Raz, Marcel Zalmanovici

Machine learning (ML) solutions are prevalent. However, many challenges exist in making these solutions business-grade. One major challenge is to ensure that the ML solution provid…

cs.LG2021

Machine Learning Model Drift Detection Via Weak Data Slices

Samuel Ackerman, Parijat Dube, Eitan Farchi +2

Detecting drift in performance of Machine Learning (ML) models is an acknowledged challenge. For ML models to become an integral part of business applications it is essential to de…