ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1810.03993
  4. Cited By
Model Cards for Model Reporting
v1v2 (latest)

Model Cards for Model Reporting

5 October 2018
Margaret Mitchell
Simone Wu
Andrew Zaldivar
Parker Barnes
Lucy Vasserman
Ben Hutchinson
Elena Spitzer
Inioluwa Deborah Raji
Timnit Gebru
ArXiv (abs)PDFHTML

Papers citing "Model Cards for Model Reporting"

50 / 415 papers shown
Title
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing
  Report Generation
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
Qingyun Wang
Manling Li
Xuan Wang
Nikolaus Nova Parulian
G. Han
...
Ahmed Elsayed
Martha Palmer
Clare Voss
Cynthia Schneider
Boyan A. Onyshkevych
60
119
0
01 Jul 2020
Survey on the Analysis and Modeling of Visual Kinship: A Decade in the
  Making
Survey on the Analysis and Modeling of Visual Kinship: A Decade in the Making
Joseph P. Robinson
Ming Shao
Y. Fu
63
6
0
29 Jun 2020
Does the Whole Exceed its Parts? The Effect of AI Explanations on
  Complementary Team Performance
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance
Gagan Bansal
Tongshuang Wu
Joyce Zhou
Raymond Fok
Besmira Nushi
Ece Kamar
Marco Tulio Ribeiro
Daniel S. Weld
125
607
0
26 Jun 2020
Supermasks in Superposition
Supermasks in Superposition
Mitchell Wortsman
Vivek Ramanujan
Rosanne Liu
Aniruddha Kembhavi
Mohammad Rastegari
J. Yosinski
Ali Farhadi
SSLCLL
111
297
0
26 Jun 2020
A Methodology for Creating AI FactSheets
A Methodology for Creating AI FactSheets
John T. Richards
David Piorkowski
Michael Hind
Stephanie Houde
Aleksandra Mojsilović
77
49
0
24 Jun 2020
Large image datasets: A pyrrhic win for computer vision?
Large image datasets: A pyrrhic win for computer vision?
Vinay Uday Prabhu
Abeba Birhane
96
367
0
24 Jun 2020
Technology Readiness Levels for AI & ML
Technology Readiness Levels for AI & ML
Alexander Lavin
Ajay Sharma
VLM
113
110
0
21 Jun 2020
Trust and Transparency in Contact Tracing Applications
Trust and Transparency in Contact Tracing Applications
S. Hobson
Michael Hind
Aleksandra Mojsilović
Kush R. Varshney
33
8
0
19 Jun 2020
Why Normalizing Flows Fail to Detect Out-of-Distribution Data
Why Normalizing Flows Fail to Detect Out-of-Distribution Data
Polina Kirichenko
Pavel Izmailov
A. Wilson
OODD
121
278
0
15 Jun 2020
Superconducting radio-frequency cavity fault classification using
  machine learning at Jefferson Laboratory
Superconducting radio-frequency cavity fault classification using machine learning at Jefferson Laboratory
C. Tennant
A. Carpenter
T. Powers
A. Solopova
Lasitha Vidyaratne
Khan M. Iftekharuddin
43
44
0
11 Jun 2020
Principles to Practices for Responsible AI: Closing the Gap
Principles to Practices for Responsible AI: Closing the Gap
Daniel S. Schiff
B. Rakova
A. Ayesh
Anat Fanti
M. Lennon
89
89
0
08 Jun 2020
Language Models are Few-Shot Learners
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
971
42,651
0
28 May 2020
Misplaced Trust: Measuring the Interference of Machine Learning in Human
  Decision-Making
Misplaced Trust: Measuring the Interference of Machine Learning in Human Decision-Making
Harini Suresh
Natalie Lao
Ilaria Liccardi
36
49
0
22 May 2020
Risk of Training Diagnostic Algorithms on Data with Demographic Bias
Risk of Training Diagnostic Algorithms on Data with Demographic Bias
Samaneh Abbasi-Sureshjani
Ralf Raumanns
B. Michels
Gerard Schouten
Veronika Cheplygina
FaML
79
37
0
20 May 2020
Social Biases in NLP Models as Barriers for Persons with Disabilities
Social Biases in NLP Models as Barriers for Persons with Disabilities
Ben Hutchinson
Vinodkumar Prabhakaran
Emily L. Denton
Kellie Webster
Yu Zhong
Stephen Denuyl
78
314
0
02 May 2020
The Grammar of Interactive Explanatory Model Analysis
The Grammar of Interactive Explanatory Model Analysis
Hubert Baniecki
Dariusz Parzych
P. Biecek
69
46
0
01 May 2020
NUBIA: NeUral Based Interchangeability Assessor for Text Generation
NUBIA: NeUral Based Interchangeability Assessor for Text Generation
Hassan Kané
Muhammed Yusuf Kocyigit
Ali Abdalla
Pelkins Ajanoh
Mohamed Coulibali
79
59
0
30 Apr 2020
REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets
REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets
Angelina Wang
Alexander Liu
Ryan Zhang
Anat Kleiman
Leslie Kim
Dora Zhao
Iroha Shirai
Arvind Narayanan
Olga Russakovsky
82
190
0
16 Apr 2020
Hiring Fairly in the Age of Algorithms
Hiring Fairly in the Age of Algorithms
Max Langenkamp
Allan dos Santos Costa
C. Y. Cheung
FaMLMLAU
46
25
0
15 Apr 2020
Entity-Switched Datasets: An Approach to Auditing the In-Domain
  Robustness of Named Entity Recognition Models
Entity-Switched Datasets: An Approach to Auditing the In-Domain Robustness of Named Entity Recognition Models
Oshin Agarwal
Yinfei Yang
Byron C. Wallace
A. Nenkova
50
23
0
08 Apr 2020
Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings
Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings
H. Zhang
Amy X. Lu
Mohamed Abdalla
Matthew B. A. McDermott
Marzyeh Ghassemi
72
176
0
11 Mar 2020
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of
  Generative Models
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
Sachit Menon
Alexandru Damian
Shijia Hu
Nikhil Ravi
Cynthia Rudin
OODDiffM
259
555
0
08 Mar 2020
The Problem with Metrics is a Fundamental Problem for AI
The Problem with Metrics is a Fundamental Problem for AI
Rachel L. Thomas
D. Uminsky
118
68
0
20 Feb 2020
Do I Look Like a Criminal? Examining how Race Presentation Impacts Human
  Judgement of Recidivism
Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism
Keri Mallari
K. Quinn
Paul Johns
Sarah Tan
Divya Ramesh
Ece Kamar
FaML
60
30
0
04 Feb 2020
How do Data Science Workers Collaborate? Roles, Workflows, and Tools
How do Data Science Workers Collaborate? Roles, Workflows, and Tools
Amy X. Zhang
Michael J. Muller
Dakuo Wang
FedMLAI4CE
115
261
0
18 Jan 2020
Lessons from Archives: Strategies for Collecting Sociocultural Data in
  Machine Learning
Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning
Eun Seo Jo
Timnit Gebru
107
317
0
22 Dec 2019
Causality matters in medical imaging
Causality matters in medical imaging
Daniel Coelho De Castro
Ian Walker
Ben Glocker
CML
59
349
0
17 Dec 2019
Towards Fairer Datasets: Filtering and Balancing the Distribution of the
  People Subtree in the ImageNet Hierarchy
Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy
Kaiyu Yang
Klint Qinami
Li Fei-Fei
Jia Deng
Olga Russakovsky
132
325
0
16 Dec 2019
AutoAIViz: Opening the Blackbox of Automated Artificial Intelligence
  with Conditional Parallel Coordinates
AutoAIViz: Opening the Blackbox of Automated Artificial Intelligence with Conditional Parallel Coordinates
D. Weidele
Justin D. Weisz
Eno Oduor
Michael J. Muller
Josh Andres
Alexander G. Gray
Dakuo Wang
94
54
0
13 Dec 2019
ABOUT ML: Annotation and Benchmarking on Understanding and Transparency
  of Machine Learning Lifecycles
ABOUT ML: Annotation and Benchmarking on Understanding and Transparency of Machine Learning Lifecycles
Inioluwa Deborah Raji
Jingyi Yang
99
38
0
12 Dec 2019
Explainability Fact Sheets: A Framework for Systematic Assessment of
  Explainable Approaches
Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches
Kacper Sokol
Peter A. Flach
XAI
119
304
0
11 Dec 2019
Women, politics and Twitter: Using machine learning to change the
  discourse
Women, politics and Twitter: Using machine learning to change the discourse
Lana Cuthbertson
Alex Kearney
R. Dawson
Ashia Zawaduk
Eve Cuthbertson
Ann Gordon-Tighe
K. Mathewson
21
10
0
25 Nov 2019
Energy Usage Reports: Environmental awareness as part of algorithmic
  accountability
Energy Usage Reports: Environmental awareness as part of algorithmic accountability
Kadan Lottick
Silvia Susai
Sorelle A. Friedler
Jonathan P. Wilson
103
57
0
19 Nov 2019
"The Human Body is a Black Box": Supporting Clinical Decision-Making
  with Deep Learning
"The Human Body is a Black Box": Supporting Clinical Decision-Making with Deep Learning
M. Sendak
M. C. Elish
M. Gao
Joseph D. Futoma
W. Ratliff
M. Nichols
A. Bedoya
S. Balu
Cara O'Brien
HAI
73
170
0
19 Nov 2019
Experiences with Improving the Transparency of AI Models and Services
Experiences with Improving the Transparency of AI Models and Services
Michael Hind
Stephanie Houde
Jacquelyn Martino
Aleksandra Mojsilović
David Piorkowski
John T. Richards
Kush R. Varshney
63
49
0
11 Nov 2019
Social Bias Frames: Reasoning about Social and Power Implications of
  Language
Social Bias Frames: Reasoning about Social and Power Implications of Language
Maarten Sap
Saadia Gabriel
Lianhui Qin
Dan Jurafsky
Noah A. Smith
Yejin Choi
165
501
0
10 Nov 2019
Predictive Biases in Natural Language Processing Models: A Conceptual
  Framework and Overview
Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview
Deven Santosh Shah
H. Andrew Schwartz
Dirk Hovy
AI4CE
126
261
0
09 Nov 2019
Fair Generative Modeling via Weak Supervision
Fair Generative Modeling via Weak Supervision
Kristy Choi
Aditya Grover
Trisha Singh
Rui Shu
Stefano Ermon
106
137
0
26 Oct 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies,
  Opportunities and Challenges toward Responsible AI
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
Alejandro Barredo Arrieta
Natalia Díaz Rodríguez
Javier Del Ser
Adrien Bennetot
Siham Tabik
...
S. Gil-Lopez
Daniel Molina
Richard Benjamins
Raja Chatila
Francisco Herrera
XAI
162
6,366
0
22 Oct 2019
Component Mismatches Are a Critical Bottleneck to Fielding AI-Enabled
  Systems in the Public Sector
Component Mismatches Are a Critical Bottleneck to Fielding AI-Enabled Systems in the Public Sector
Grace A. Lewis
S. Bellomo
April Galyardt
43
6
0
14 Oct 2019
The Bouncer Problem: Challenges to Remote Explainability
The Bouncer Problem: Challenges to Remote Explainability
Erwan Le Merrer
Gilles Tredan
60
8
0
03 Oct 2019
Predictive Multiplicity in Classification
Predictive Multiplicity in Classification
Charles Marx
Flavio du Pin Calmon
Berk Ustun
136
147
0
14 Sep 2019
CTRL: A Conditional Transformer Language Model for Controllable
  Generation
CTRL: A Conditional Transformer Language Model for Controllable Generation
N. Keskar
Bryan McCann
Lav Varshney
Caiming Xiong
R. Socher
AI4CE
146
1,254
0
11 Sep 2019
ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia
ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia
Aaron L Halfaker
R. Geiger
AI4TSKELM
135
20
0
11 Sep 2019
Pretrained AI Models: Performativity, Mobility, and Change
Pretrained AI Models: Performativity, Mobility, and Change
Lav Varshney
N. Keskar
R. Socher
68
20
0
07 Sep 2019
Show Your Work: Improved Reporting of Experimental Results
Show Your Work: Improved Reporting of Experimental Results
Jesse Dodge
Suchin Gururangan
Dallas Card
Roy Schwartz
Noah A. Smith
78
255
0
06 Sep 2019
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDaFaML
603
4,414
0
23 Aug 2019
Making Neural Networks FAIR
Making Neural Networks FAIR
Anna Nguyen
T. Weller
Michael Färber
York Sure-Vetter
38
11
0
26 Jul 2019
TED-On: A Total Error Framework for Digital Traces of Human Behavior on
  Online Platforms
TED-On: A Total Error Framework for Digital Traces of Human Behavior on Online Platforms
Indira Sen
Fabian Flöck
Katrin Weller
Bernd Weiss
Claudia Wagner
60
50
0
18 Jul 2019
Quantifying Transparency of Machine Learning Systems through Analysis of
  Contributions
Quantifying Transparency of Machine Learning Systems through Analysis of Contributions
I. Barclay
Alun D. Preece
Ian J. Taylor
D. Verma
26
5
0
08 Jul 2019
Previous
123456789
Next