From the 1 of 4 linked papers with an AI index.
4 papers
Drawing-Recode: Annotation Grounding for Parametric CAD Code Generation from Raster 2D CAD Drawings
Mingi Kim, Yongjun Kim, Hyungki Kim
Drawing-Recode is a system that converts raster 2D CAD drawings into parametric CAD code by extracting geometric features, recognizing textual annotations, grounding the annotation…
PARTREP: Learning What to Repeat for Decoder-only LLMs
Andikawati P Widjaja, Yongjun Kim, Hyounghun Kim +1
While decoder-only LLMs excel at a vast array of natural language tasks, it suffers from an asymmetric information flow induced by causal attention: later tokens are richer in cont…
BrepCoder: A Unified Multimodal Large Language Model for Multi-task B-rep Reasoning
Mingi Kim, Yongjun Kim, Jungwoo Kang +1
Recent advancements in deep learning have actively addressed complex challenges within the Computer-Aided Design (CAD) domain.However, most existing approaches rely on task-specifi…
ZIP: An Efficient Zeroth-order Prompt Tuning for Black-box Vision-Language Models
Seonghwan Park, Jaehyeon Jeong, Yongjun Kim +2
Recent studies have introduced various approaches for prompt-tuning black-box vision-language models, referred to as black-box prompt-tuning (BBPT). While BBPT has demonstrated con…