Hallucinating to better text translation
A machine-learning method imagines what a sentence visually looks like, to situate and ground its semantics in the real world, improving translation, like humans can.
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A machine-learning method imagines what a sentence visually looks like, to situate and ground its semantics in the real world, improving translation, like humans can.
Researchers have created prototypes that enable screen-reader users to quickly and easily navigate through multiple levels of information in an online chart.
Explanation methods that help users determine whether to trust machine-learning model predictions can be less accurate for disadvantaged subgroups, a new study finds.
Known as a visionary who brought together faculty from across MIT, Moses pioneered an influential symbolic mathematics program and held many top leadership posts.
Security Studies Program offers knowledge on national security issues.
With modular components and an easy-to-use 3D interface, this interactive design pipeline enables anyone to create their own customized robotic hand.
Study shows AI can identify self-reported race from medical images that contain no indications of race detectable by human experts.
A new technique can safely guide an autonomous robot without knowledge of its environmental conditions or the size, shape, or location of obstacles it might encounter.
MIT and Mass General Brigham researchers and physicians connect in person to bring AI into mainstream health care.
Faculty members Angela Belcher, Pablo Jarillo-Herrero, and Ronitt Rubinfeld elected by peers for outstanding contributions to research.
Researchers devise an efficient protocol to keep a user’s private information secure when algorithms use it to recommend products, songs, or shows.
Have a question about numerical differential equations? Odds are this CSAIL research affiliate has already addressed it.
Researchers create a mathematical framework to evaluate explanations of machine-learning models and quantify how well people understand them.
A machine-learning model can identify the action in a video clip and label it, without the help of humans.
Natural language processing models capture rich knowledge of words’ meanings through statistics.