6 citations · 13 across the 12 of their papers we have counts for
13 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…
EyeBrain: Left and Right Brain Lateralization Activity Classification Through Pupil Diameter and Fixation Duration
Ko Watanabe, Pooja Pol, Nicolas Großmann +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…
Push or Light: Nudging Standing to Break Prolonged Sitting
Sohshi Yoshida, Ko Watanabe, Andreas Dengel +3
Prolonged sitting is a health risk leading to metabolic and cardiovascular diseases. To combat this, various "nudging" strategies encourage stand-ups. Behavior change triggers use…
TrackThinkDashboard: Understanding Student Self-Regulated Learning in Programming Study
Ko Watanabe, Yuki Matsuda, Yugo Nakamura +2
In programming education, fostering self-regulated learning (SRL) skills is essential for both students and teachers. This paper introduces TrackThinkDashboard, an application desi…
GenAIReading: Augmenting Human Cognition with Interactive Digital Textbooks Using Large Language Models and Image Generation Models
Ryugo Morita, Ko Watanabe, Jinjia Zhou +2
Cognitive augmentation is a cornerstone in advancing education, particularly through personalized learning. However, personalizing extensive textual materials, such as narratives a…
Augmenting Online Meetings with Context-Aware Real-time Music Generation
Haruki Suzawa, Ko Watanabe, Andreas Dengel +1
As online communication continues to expand, participants often face cognitive fatigue and reduced engagement. Cognitive augmentation, which leverages technology to enhance human a…
SensPS: Sensing Personal Space Comfortable Distance between Human-Human Using Multimodal Sensors
Ko Watanabe, Nico Förster, Shoya Ishimaru
Personal space, also known as peripersonal space, is crucial in human social interaction, influencing comfort, communication, and social stress. Estimating and respecting personal…
Human-in-the-Loop Annotation for Image-Based Engagement Estimation: Assessing the Impact of Model Reliability on Annotation Accuracy
Sahana Yadnakudige Subramanya, Ko Watanabe, Andreas Dengel +1
Human-in-the-loop (HITL) frameworks are increasingly recognized for their potential to improve annotation accuracy in emotion estimation systems by combining machine predictions wi…
Skewness consistency relation in large-scale structure and test of gravity theory
Daisuke Yamauchi, Shoya Ishimaru, Takahiko Matsubara +1
We investigate the skewness of galaxy number density fluctuations as a possible probe to test gravity theories. We find that the specific linear combination of the skewness paramet…
What Do We Get from Two-Way Fixed Effects Regressions? Implications from Numerical Equivalence
Shoya Ishimaru
This paper develops numerical and causal interpretations of two-way fixed effects (TWFE) regressions in settings with nonbinary, nonstaggered treatments and time-varying covariates…
Confidence-Aware Learning Assistant
Shoya Ishimaru, Takanori Maruichi, Andreas Dengel +1
Not only correctness but also self-confidence play an important role in improving the quality of knowledge. Undesirable situations such as confident incorrect and unconfident corre…
Empirical Decomposition of the IV-OLS Gap with Heterogeneous and Nonlinear Effects
Shoya Ishimaru
This study proposes an econometric framework to interpret and empirically decompose the difference between IV and OLS estimates given by a linear regression model when the true cau…