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A Meta-Summary of Challenges in Building Products with ML Components -- Collecting Experiences from 4758+ Practitioners
31 March 2023
Nadia Nahar
Haoran Zhang
Grace A. Lewis
Shurui Zhou
Christian Kastner
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Papers citing
"A Meta-Summary of Challenges in Building Products with ML Components -- Collecting Experiences from 4758+ Practitioners"
11 / 11 papers shown
Title
Prompts Are Programs Too! Understanding How Developers Build Software Containing Prompts
Jenny T Liang
Melissa Lin
Nikitha Rao
Brad A. Myers
77
5
0
19 Sep 2024
A Large-Scale Study of Model Integration in ML-Enabled Software Systems
Yorick Sens
Henriette Knopp
Sven Peldszus
Thorsten Berger
AIFin
31
2
0
12 Aug 2024
Naming the Pain in Machine Learning-Enabled Systems Engineering
Marcos Kalinowski
Daniel Méndez
G. Giray
Antonio Pedro Santos Alves
Kelly Azevedo
...
Stefan Biffl
Jürgen Musil
Michael Felderer
N. Lavesson
T. Gorschek
24
5
0
20 May 2024
How to Sustainably Monitor ML-Enabled Systems? Accuracy and Energy Efficiency Tradeoffs in Concept Drift Detection
Rafiullah Omar
Justus Bogner
J. Leest
Vincenzo Stoico
Patricia Lago
H. Muccini
17
1
0
30 Apr 2024
Beyond Testers' Biases: Guiding Model Testing with Knowledge Bases using LLMs
Chenyang Yang
Rishabh Rustogi
Rachel A. Brower-Sinning
Grace A. Lewis
Christian Kastner
Tongshuang Wu
KELM
35
12
0
14 Oct 2023
From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible ML
Shalaleh Rismani
Renee Shelby
A. Smart
Edgar W. Jatho
Joshua A. Kroll
AJung Moon
Negar Rostamzadeh
42
36
0
06 Oct 2022
Operationalizing Machine Learning: An Interview Study
Shreya Shankar
Rolando Garcia
J. M. Hellerstein
Aditya G. Parameswaran
71
51
0
16 Sep 2022
Towards Guidelines for Assessing Qualities of Machine Learning Systems
Julien Siebert
Lisa Joeckel
J. Heidrich
K. Nakamichi
Kyoko Ohashi
I. Namba
Rieko Yamamoto
M. Aoyama
28
47
0
25 Aug 2020
Trust in Data Science: Collaboration, Translation, and Accountability in Corporate Data Science Projects
Samir Passi
S. Jackson
171
108
0
09 Feb 2020
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI
Dakuo Wang
Justin D. Weisz
Michael J. Muller
Parikshit Ram
Werner Geyer
Casey Dugan
Y. Tausczik
Horst Samulowitz
Alexander G. Gray
178
308
0
05 Sep 2019
Improving fairness in machine learning systems: What do industry practitioners need?
Kenneth Holstein
Jennifer Wortman Vaughan
Hal Daumé
Miroslav Dudík
Hanna M. Wallach
FaML
HAI
192
743
0
13 Dec 2018
1