6 citations · 8 across the 3 of their papers we have counts for
3 papers
Beyond Testers' Biases: Guiding Model Testing with Knowledge Bases using LLMs
Chenyang Yang, Rishabh Rustogi, Rachel Brower-Sinning +3
Current model testing work has mostly focused on creating test cases. Identifying what to test is a step that is largely ignored and poorly supported. We propose Weaver, an interac…
A Meta-Summary of Challenges in Building Products with ML Components -- Collecting Experiences from 4758+ Practitioners
Nadia Nahar, Haoran Zhang, Grace Lewis +2
Incorporating machine learning (ML) components into software products raises new software-engineering challenges and exacerbates existing challenges. Many researchers have invested…
MLTEing Models: Negotiating, Evaluating, and Documenting Model and System Qualities
Katherine R. Maffey, Kyle Dotterrer, Jennifer Niemann +3
Many organizations seek to ensure that machine learning (ML) and artificial intelligence (AI) systems work as intended in production but currently do not have a cohesive methodolog…