3 citations · 6 across the 7 of their papers we have counts for
7 papers
Shallow-π: Knowledge Distillation for Flow-based VLAs
Boseong Jeon, Yunho Choi, Taehan Kim
The growing demand for real-time robotic deployment necessitates fast and on-device inference for vision-language-action (VLA) models. Within the VLA literature, efficiency has bee…
InvThink: Premortem Reasoning for Safer Language Models
Yubin Kim, Taehan Kim, Eugene Park +4
We present InvThink, a training and prompting framework that requires the model to enumerate, analyze, and constrain potential failures before generating its final response. Unlike…
No Encore: Unlearning as Opt-Out in Music Generation
Jinju Kim, Taehan Kim, Abdul Waheed +2
AI music generation is rapidly emerging in the creative industries, enabling intuitive music generation from textual descriptions. However, these systems pose risks in exploitation…
VocalAgent: Large Language Models for Vocal Health Diagnostics with Safety-Aware Evaluation
Yubin Kim, Taehan Kim, Wonjune Kang +8
Vocal health plays a crucial role in peoples' lives, significantly impacting their communicative abilities and interactions. However, despite the global prevalence of voice disorde…
HiPPO-KAN: Efficient KAN Model for Time Series Analysis
SangJong Lee, Jin-Kwang Kim, JunHo Kim +2
In this study, we introduces a parameter-efficient model that outperforms traditional models in time series forecasting, by integrating High-order Polynomial Projection (HiPPO) the…
A Knowledge-Component-Based Methodology for Evaluating AI Assistants
Laryn Qi, J. D. Zamfirescu-Pereira, Taehan Kim +3
We evaluate an automatic hint generator for CS1 programming assignments powered by GPT-4, a large language model. This system provides natural language guidance about how students…
Diffusion-EDFs: Bi-equivariant Denoising Generative Modeling on SE(3) for Visual Robotic Manipulation
Hyunwoo Ryu, Jiwoo Kim, Hyunseok An +7
Diffusion generative modeling has become a promising approach for learning robotic manipulation tasks from stochastic human demonstrations. In this paper, we present Diffusion-EDFs…