Fetching the paper…
Reading the bibliography…
As research and industry moves towards large-scale models capable of numerous downstream tasks, the complexity of understanding multi-modal datasets that give nuance to models rapidly increases.
The open images dataset v4
Alina Kuznetsova, Hassan Rom, Neil Alldrin, Jasper Uijlings, Ivan Krasin, Jordi Pont-Tuset, Shahab Kamali, Stefan Popov, Matteo Malloci, Alexander Kolesnikov, et al · 1981
Earlier work this paper cites.
Institutional ecology,translations’ and boundary objects: Amateurs and professionals in Berkeley’s Museum of Vertebrate Zoology, 1907-39
Susan Leigh Star and James R Griesemer. 1989 · 1989
Earlier work this paper cites.
The eyes have it: A task by data type taxonomy for information visualizations
Ben Shneiderman. 2003 · 2003
Earlier work this paper cites.
This is not a boundary object: Reflections on the origin of a concept
Susan Leigh Star. 2010 · 2010
Earlier work this paper cites.
Data mining and predictive analysis: Intelligence gathering and crime analysis
Colleen McCue. 2014 · 2014
Earlier work this paper cites.
AI Now Institute
2017 · 2017
Earlier work this paper cites.
Fairness and transparency of machine learning for trustworthy cloud services. In 2018 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W) . IEEE, 188–193
Nuno Antunes, Leandro Balby, Flavio Figueiredo, Nuno Lourenco, Wagner Meira, and Walter Santos. 2018 · 2018
Earlier work this paper cites.
Data statements for natural language processing: Toward mitigating system bias and enabling better science
Emily M Bender and Batya Friedman. 2018 · 2018
Earlier work this paper cites.
Working with beliefs: AI transparency in the enterprise. In IUI Workshops
Ajay Chander, Ramya Srinivasan, Suhas Chelian, Jun Wang, and Kanji Uchino. 2018 · 2018
Earlier work this paper cites.
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, and Kate Crawford. 2018 · 2018
Cited alongside, same era.
Model cards for model reporting. In Proceedings of the conference on fairness, accountability, and transparency . 220–229
Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, and Timnit Gebru. 2019 · 2019
Cited alongside, same era.
Open Images Extended - Crowdsourced Data Card
Parker Barnes Anurag Batra. 2020 · 2020
Cited alongside, same era.
A framework for fostering transparency in shared artificial intelligence models by increasing visibility of contributions
Iain Barclay, Harrison Taylor, Alun Preece, Ian Taylor, Dinesh Verma, and Geeth de Mel. 2020 · 2020
Cited alongside, same era.
Towards transparency by design for artificial intelligence
Heike Felzmann, Eduard Fosch-Villaronga, Christoph Lutz, and Aurelia Tamò-Larrieux. 2020 · 2020
Candice chumann, Susanna Ricco, Utsav Prabhu, Vittorio Ferrari, and Caroline Pantofaru. 2021
2021
Later among the works it cites.
Expanding explainability: Towards social transparency in ai systems. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems . 1–19
Upol Ehsan, Q Vera Liao, Michael Muller, Mark O Riedl, and Justin D Weisz. 2021 · 2021
Later among the works it cites.
HuggingFace - Create a Dataset Card
HuggingFace. 2021 · 2021
Later among the works it cites.
Towards accountability for machine learning datasets: Practices from software engineering and infrastructure. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency . 560–575
Ben Hutchinson, Andrew Smart, Alex Hanna, Emily Denton, Christina Greer, Oddur Kjartansson, Parker Barnes, and Margaret Mitchell. 2021 · 2021
Later among the works it cites.
Data Cards Playbook: Participatory Activities for Dataset Documentation
Mahima Pushkarna, Andrew Zaldivar, and Daniel Nanas. [n. d.] · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
2021 · 2021
Cited alongside, same era.
Enabling AI with Data Cards
Joint Artificial Intelligence Center Public Affairs. 2021 · 2021
Cited alongside, same era.
Anja Austermann, Michelle Linch, Romina Stella, and Kellie Webster. 2021
2021
Cited alongside, same era.
Uncertainty as a form of transparency: Measuring, communicating, and using uncertainty. In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society . 401–413
Umang Bhatt, Javier Antorán, Yunfeng Zhang, Q Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Melançon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, et al · 2021
Cited alongside, same era.
Later among the works it cites.
Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems . 1–16
Harini Suresh, Steven R Gomez, Kevin K Nam, and Arvind Satyanarayan. 2021 · 2021
Later among the works it cites.
Natural Language Generation, its Evaluation and Metrics Data Cards
GEM. 2022 · 2022
Closest in time.
Know Your Data
People + AI Research Initiative. 2022 · 2022
Closest in time.