10 citations · 10 across the 5 of their papers we have counts for
5 papers
SpecialEduBench: Benchmarking Vision-Language Models on Knowledge, Skill, and Attitude in Language Intervention for Autistic Children
Jihoi Na, Taeyeong Kim, Sungjune Kong +11
Language is the target of most early intervention for autistic children. Because the goal and the method change from child to child, the work falls to a teacher who takes one child…
Not the Dimension, the Norm: What Matters in Gradient-Free Weight Perturbation of Language Models
Taeyeong Kim, Ahhyun Kim, TaeHyeon Kim +1
Adapting a language model to a task no longer requires training all of its weights, and a line of parameter-efficient methods has driven the trainable count from billions down to a…
Visual-RRT: Finding Paths toward Visual-Goals via Differentiable Rendering
Sebin Lee, Jumin Lee, Taeyeon Kim +3
Rapidly-exploring random trees (RRTs) have been widely adopted for robot motion planning due to their robustness and theoretical guarantees. However, existing RRT-based planners re…
Pedagogical Alignment for Vision-Language-Action Models: A Comprehensive Framework for Data, Architecture, and Evaluation in Education
Unggi Lee, Jahyun Jeong, Sunyoung Shin +12
Science demonstrations are important for effective STEM education, yet teachers face challenges in conducting them safely and consistently across multiple occasions, where robotics…
An Addendum to NeBula: Towards Extending TEAM CoSTAR's Solution to Larger Scale Environments
Ali Agha, Kyohei Otsu, Benjamin Morrell +86
This paper presents an appendix to the original NeBula autonomy solution developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), participating in the DARPA Sub…