mlsanityData to 7 Oct 2026

DAG Card is the new Model Card

arXiv 2110.13601 ↗First posted 24 Oct 2021cs.SE cs.LGcited by 5

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Abstract (arXiv)

With the progressive commoditization of modeling capabilities, data-centric AI recognizes that what happens before and after training becomes crucial for real-world deployments. Following the intuition behind Model Cards, we propose DAG Cards as a form of documentation encompassing the tenets of a data-centric point of view. We argue that Machine Learning pipelines (rather than models) are the most appropriate level of documentation for many practical use cases, and we share with the community an open implementation to generate cards from code.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 6 of its 22 references that are in the map. First posted on arXiv 24 Oct 2021.

Builds on

6 of 22 references.

References · 6

  1. 2020Scaling Laws for Neural Language Modelscited by 6,411
  2. 2018Model Cards for Model Reportingcited by 1,068
  3. 2020Beyond Accuracy: Behavioral Testing of NLP models with CheckListcited by 979
  4. 2021Changing the World by Changing the Datacited by 51
  5. 2021You Do Not Need a Bigger Boat: Recommendations at Reasonable Scale in a (Mostly) Serverless and Open Stackcited by 5
  6. 2021"Are you sure?": Preliminary Insights from Scaling Product Comparisons to Multiple Shopscited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 1; 2026: 1.

5 papers.