3 papers
cs.CV2026
GuideCAD: A Lightweight Multimodal Framework for 3D CAD Model Generation via Prefix Embedding
Minseong Kim, Jinyeong Park, Sungho Park +1
Multi-modal approaches used for 3D CAD generation require substantial computational resources, necessitating efficient training. To address this, we propose GuideCAD, which leverag…
cs.CV2026
QATMA: Quantization-Aware Training with Multimodal Alignment for Open-Vocabulary Object Detection
Jinyeong Park, Donghwa Kang, Brent ByungHoon Kang +4
Quantizing open-vocabulary object detection (OVOD) models reduces their memory and computational costs, but extremely low-bit quantization severely degrades both cross-modal (regio…
cs.LG2026
CAMEL-CLIP: Channel-aware Multimodal Electroencephalography-text Alignment for Generalizable Brain Foundation Models
Hanseul Choi, Jinyeong Park, Seongwon Jin +2
Electroencephalography (EEG) foundation models have shown promise for learning generalizable representations, yet they remain sensitive to channel heterogeneity, such as changes in…