0 papers in the Vision Foundation Models Evaluation research area.
Discover 1 peer-reviewed study in Vision Foundation Models Evaluation (2024). Explore research findings powered by Prolific's diverse participant panel.
This page lists 1 peer-reviewed paper in the research area of Vision Foundation Models Evaluation in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.
Authors: M Ku, T Li, K Zhang, Y Lu, X Fu, W Zhuang
Year: 2024
Published in: - arXiv preprint arXiv …, 2023 - arxiv.org
Institution: University of Waterloo, Ohio State University, University of California Santa Barbara, University of Pensylvania
Research Area: AI alignment, Representation learning, Cognitive computational modeling, Vision foundation models evaluation, Multimodal, Vision models
Discipline: Computer Science, Artificial Intelligence, Machine Learning
This paper presents a method for **aligning machine vision model representations with human visual similarity judgments across different abstraction levels, improving how well models reflect human perceptual and conceptual organization and enhancing generalization and uncertainty prediction.
DOI: https://doi.org/10.48550/arXiv.2310.01596
Citations: 59
Related Disciplines: Computer Science, Artificial Intelligence, Machine Learning
Related Institutions: University of Waterloo, Ohio State University, University of California Santa Barbara, University of Pensylvania
Researchers: M Ku, T Li, K Zhang, Y Lu, X Fu
Publication Years: 2024
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