activity
20192026
most citedDeep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials

120 citations · 122 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

K-EXAONE 2.0 Technical Report

Eunbi Choi, Kibong Choi, Sehyun Chun +74

This technical report presents K-EXAONE 2.0, an open-weight multilingual foundation model developed by LG AI Research as a step in our effort toward global frontier-scale foundatio…

cs.CL2026

EXAONE 4.5 Technical Report

Eunbi Choi, Kibong Choi, Sehyun Chun +55

This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integrating a dedicated visual enc…

cs.LG2025★ 1 cited

MolMole: Molecule Mining from Scientific Literature

LG AI Research, Sehyun Chun, Jiye Kim +31

The extraction of molecular structures and reaction data from scientific documents is challenging due to their varied, unstructured chemical formats and complex document layouts. T…

cond-mat.mtrl-sci2020★ 120 cited

Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials

Sehyun Chun, Sidhartha Roy, Yen Thi Nguyen +3

The sensitivity of heterogeneous energetic (HE) materials (propellants, explosives, and pyrotechnics) is critically dependent on their microstructure. Initiation of chemical reacti…

cs.CV2019★ 1 cited

NADS-Net: A Nimble Architecture for Driver and Seat Belt Detection via Convolutional Neural Networks

Sehyun Chun, Nima Hamidi Ghalehjegh, Joseph B. Choi +4

A new convolutional neural network (CNN) architecture for 2D driver/passenger pose estimation and seat belt detection is proposed in this paper. The new architecture is more nimble…