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Liunian Li – ProQuest LLC, 2024
To build an Artificial Intelligence system that can assist us in daily lives, the ability to understand the world around us through visual input is essential. Prior studies train visual perception models by defining concept vocabularies and annotate data against the fixed vocabulary. It is hard to define a comprehensive set of everything, and thus…
Descriptors: Artificial Intelligence, Visual Stimuli, Visual Perception, Models
Peer reviewed Peer reviewed
Sami Baral; Li Lucy; Ryan Knight; Alice Ng; Luca Soldaini; Neil T. Heffernan; Kyle Lo – Grantee Submission, 2024
In real-world settings, vision language models (VLMs) should robustly handle naturalistic, noisy visual content as well as domain-specific language and concepts. For example, K-12 educators using digital learning platforms may need to examine and provide feedback across many images of students' math work. To assess the potential of VLMs to support…
Descriptors: Visual Learning, Visual Perception, Natural Language Processing, Freehand Drawing
Peer reviewed Peer reviewed
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Ní Chiaráin, Neasa; Ní Chasaide, Ailbhe – Research-publishing.net, 2019
A key benefit in intelligent Computer Assisted Language Learning (iCALL) is that it allows complex linguistic phenomena to be incorporated into digital learning platforms, either for the autonomous learner or to complement classroom teaching. The present paper describes (1) complex phonological/ morphophonemic alternations of Irish, which are…
Descriptors: Computer Assisted Instruction, Educational Technology, Technology Uses in Education, Second Language Learning