A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs
Science, 2017. [All Versions]. [Preprint]. Learning from a few examples and generalizing to markedly different situations are capabilities of human visual intelligence that are yet to be matched by leading machine learning models. By drawing inspiration from systems…
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Visual Concept Programming: A Visual Analytics Approach to Injecting Human Intelligence at Scale ieeexplore.ieee.org
IEEE Transactions on Visualization and Computer Graphics, 2023. [All Versions]. This paper presents Visual Concept Programming, a first-of-its-kind visual analytics approach of using visual concepts to program image data at scale while requiring a few human efforts.
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Building Machines That Learn and Think Like People cambridge.org
Behavioral and Brain Sciences, 2017. [All Versions]. [Preprint]. Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as…
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Generating new concepts with hybrid neuro-symbolic models. arxiv.org
CogSci'20, 2020. [All Versions].
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Learning Task-General Representations with Generative Neuro-Symbolic Modeling arxiv.org
ICLR'21, 2021. [All Versions].
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Visual Programming: Compositional Visual Reasoning Without Training openaccess.thecvf.com
CVPR'23, 2023. [All Versions]. VISPROG, a neuro-symbolic approach to solving complex and compositional visual tasks given natural language instructions, using the in-context learning ability of large language models to generate python-like modular programs, which are then…
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computer-vision-in-action github.com
AGI & CoCoSci › Papers > Bayesian Modeling > Generative Model: “Science, 2017. [All Versions]. [Preprint]. Learning from a few examples and generalizing to markedly different situations are capabilities of human visual intelligence that are yet to be matched by leading machine learning models. By drawing inspiration from systems…”