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Konferenzbeitrag

Hard to Cheat: A Turing Test based on Answering Questions about Images

MPG-Autoren
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Malinowski,  Mateusz
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society;

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Fritz,  Mario
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society;

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Zitation

Malinowski, M., & Fritz, M. (in press). Hard to Cheat: A Turing Test based on Answering Questions about Images. In Twenty-Ninth AAAI Conference on Artificial Intelligence W6, Beyond the Turing Test.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0024-9358-8
Zusammenfassung
Progress in language and image understanding by machines has sparkled the interest of the research community in more open-ended, holistic tasks, and refueled an old AI dream of building intelligent machines. We discuss a few prominent challenges that characterize such holistic tasks and argue for "question answering about images" as a particular appealing instance of such a holistic task. In particular, we point out that it is a version of a Turing Test that is likely to be more robust to over-interpretations and contrast it with tasks like grounding and generation of descriptions. Finally, we discuss tools to measure progress in this field.