Sunnie S. Y. Kim

Orcid: 0000-0002-8901-7233

Affiliations:
  • Princeton University, NJ, USA
  • Toyota Technological Institute, Chicago, IL, USA


According to our database1, Sunnie S. Y. Kim authored at least 13 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2023
WiCV@CVPR2023: The Eleventh Women In Computer Vision Workshop at the Annual CVPR Conference.
CoRR, 2023

UFO: A unified method for controlling Understandability and Faithfulness Objectives in concept-based explanations for CNNs.
CoRR, 2023

Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Application.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Overlooked Factors in Concept-Based Explanations: Dataset Choice, Concept Learnability, and Human Capability.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

"Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interaction.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

2022
Overlooked factors in concept-based explanations: Dataset choice, concept salience, and human capability.
CoRR, 2022

ELUDE: Generating interpretable explanations via a decomposition into labelled and unlabelled features.
CoRR, 2022

HIVE: Evaluating the Human Interpretability of Visual Explanations.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
Cleaning and Structuring the Label Space of the iMet Collection 2020.
CoRR, 2021

[Re] Don't Judge an Object by Its Context: Learning to Overcome Contextual Bias.
CoRR, 2021

Information-Theoretic Segmentation by Inpainting Error Maximization.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Fair Attribute Classification Through Latent Space De-Biasing.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Deformable Style Transfer.
Proceedings of the Computer Vision - ECCV 2020, 2020


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