Zobrazeno 1 - 10
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pro vyhledávání: '"Denton, Emily"'
The unstructured nature of data used in foundation model development is a challenge to systematic analyses for making data use and documentation decisions. From a Responsible AI perspective, these decisions often rely upon understanding how people ar
Externí odkaz:
http://arxiv.org/abs/2311.17259
Autor:
Muller, Emily, Gemmell, Emily, Choudhury, Ishmam, Nathvani, Ricky, Metzler, Antje Barbara, Bennett, James, Denton, Emily, Flaxman, Seth, Ezzati, Majid
The interactions of individuals with city neighbourhoods is determined, in part, by the perceived quality of urban environments. Perceived neighbourhood quality is a core component of urban vitality, influencing social cohesion, sense of community, s
Externí odkaz:
http://arxiv.org/abs/2211.12139
Autor:
Diaz, Mark, Kivlichan, Ian D., Rosen, Rachel, Baker, Dylan K., Amironesei, Razvan, Prabhakaran, Vinodkumar, Denton, Emily
Human annotated data plays a crucial role in machine learning (ML) research and development. However, the ethical considerations around the processes and decisions that go into dataset annotation have not received nearly enough attention. In this pap
Externí odkaz:
http://arxiv.org/abs/2206.08931
Autor:
Saharia, Chitwan, Chan, William, Saxena, Saurabh, Li, Lala, Whang, Jay, Denton, Emily, Ghasemipour, Seyed Kamyar Seyed, Ayan, Burcu Karagol, Mahdavi, S. Sara, Lopes, Rapha Gontijo, Salimans, Tim, Ho, Jonathan, Fleet, David J, Norouzi, Mohammad
We present Imagen, a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding. Imagen builds on the power of large transformer language models in understanding text and hinges on the streng
Externí odkaz:
http://arxiv.org/abs/2205.11487
Publikováno v:
NeurIPS 2021 workshop on Machine Learning for Creativity and Design
This paper offers a retrospective of what we learnt from organizing the workshop *Ethical Considerations in Creative applications of Computer Vision* at CVPR 2021 conference and, prior to that, a series of workshops on *Computer Vision for Fashion, A
Externí odkaz:
http://arxiv.org/abs/2112.03111
Benchmark datasets play a central role in the organization of machine learning research. They coordinate researchers around shared research problems and serve as a measure of progress towards shared goals. Despite the foundational role of benchmarkin
Externí odkaz:
http://arxiv.org/abs/2112.01716
There is a tendency across different subfields in AI to valorize a small collection of influential benchmarks. These benchmarks operate as stand-ins for a range of anointed common problems that are frequently framed as foundational milestones on the
Externí odkaz:
http://arxiv.org/abs/2111.15366
Publikováno v:
Proc. ACM Hum.-Comput. Interact.5, CSCW2, Article 317(October 2021), 37 pages
Data is a crucial component of machine learning. The field is reliant on data to train, validate, and test models. With increased technical capabilities, machine learning research has boomed in both academic and industry settings, and one major focus
Externí odkaz:
http://arxiv.org/abs/2108.04308
Publikováno v:
Patterns, Volume 2, Issue 11, 100336. 2021
Datasets have played a foundational role in the advancement of machine learning research. They form the basis for the models we design and deploy, as well as our primary medium for benchmarking and evaluation. Furthermore, the ways in which we collec
Externí odkaz:
http://arxiv.org/abs/2012.05345
Autor:
Hutchinson, Ben, Smart, Andrew, Hanna, Alex, Denton, Emily, Greer, Christina, Kjartansson, Oddur, Barnes, Parker, Mitchell, Margaret
Rising concern for the societal implications of artificial intelligence systems has inspired demands for greater transparency and accountability. However the datasets which empower machine learning are often used, shared and re-used with little visib
Externí odkaz:
http://arxiv.org/abs/2010.13561