18 papers
Can AI Guess What You Know? Performance Comparison of Large Language Models for Human Domain Knowledge Estimation From Communication Logs
Ko Watanabe, Shoya Ishimaru
Employees often struggle to identify ``who knows what,'' leading to organizational productivity losses. We investigate whether Large Language Models (LLMs) can infer individual dom…
LimeCross: Context-Conditioned Layered Image Editing with Structural Consistency
Ryugo Morita, Stanislav Frolov, Brian Bernhard Moser +4
Layered image assets are widely used in real-world creative workflows, enabling non-destructive iteration and flexible re-composition. Recent advances in layered image generation a…
EyeBrain: Left and Right Brain Lateralization Activity Classification Through Pupil Diameter and Fixation Duration
Ko Watanabe, Pooja Pol, Nicolas GroÃmann +2
The relationship between brain lateralization and cognitive functions is well-documented. The left hemisphere primarily handles tasks such as language and arithmetic, while the rig…
Empowering Vocabulary Learning Through Teaching AI: Using LLMs as a Student to Perform Learning by Teaching in Vocabulary Acquisition
Tokio Uchida, Ko Watanabe, Andrew Vargo +5
"Learning by Teaching (LbT)" helps learners deepen their understanding by explaining concepts to others, with questions playing a vital role in identifying knowledge gaps and reinf…
HandyLabel: Towards Post-Processing to Real-Time Annotation Using Skeleton Based Hand Gesture Recognition
Sachin Kumar Singh, Ko Watanabe, Brian Moser +2
The success of machine learning is deeply linked to the availability of high-quality training data, yet retrieving and manually labeling new data remains a time-consuming and error…
LGTM: Training-Free Light-Guided Text-to-Image Diffusion Model via Initial Noise Manipulation
Ryugo Morita, Stanislav Frolov, Brian Bernhard Moser +3
Diffusion models have demonstrated high-quality performance in conditional text-to-image generation, particularly with structural cues such as edges, layouts, and depth. However, l…