Scientific Frontiers
Beyond Scaling Laws
Physical AI & Robotic Foundation Models
High-dimensional Generative Foundation Models
Research Archive
Governance
Organization & Structure
Leadership
Strategic Advisors Board
Ecosystem
Academic Consortium
Industry Alliances
Public Sector Partners
Global Research Network
Knowledge Hub
Media
Symposia & Open Labs
Seminars
Newsletter
About NAIRL
Mission & Vision
Team
Facilities & Contact
EN
·
KO
Join us
EN
·
KO
Join us
esc
Beyond Scaling Laws
Physical AI & Robotic Foundation Models
High-dimensional Generative Foundation Models
Research Archive
선도 연구 주제
전체 논문
NAIRL이 세 가지 선도 연구 주제에 걸쳐 발표한 연구의 전체 색인입니다.
←
연구 아카이브로 돌아가기
All
317
Beyond Scaling Laws
155
Physical AI & Robotics
104
High-dimensional Generative Models
58
전체 논문
논문 317개
# High-dimensional Generative Foundation Models
Chain-of-Zoom: Extreme Super-Resolution via Scale Autoregression and Preference Alignment
Bryan Sangwoo Kim, Jeongsol Kim, Jong Chul Ye ·
NeurIPS
· 2025
# High-dimensional Generative Foundation Models
Aligning Text to Image in Diffusion Models is Easier Than You Think
Jaa-Yeon Lee, Byunghee Cha, Jeongsol Kim, Jong Chul Ye ·
NeurIPS
· 2025
# High-dimensional Generative Foundation Models
Inference-Time Diffusion Model Distillation
Geon Yeong Park, Sang Wan Lee, Jong Chul Ye ·
ICCV
· 2025
# High-dimensional Generative Foundation Models
FlowDPS : Flow-Driven Posterior Sampling for Inverse Problems
Jeongsol Kim, Bryan Sangwoo Kim, Jong Chul Ye ·
ICCV
· 2025
# High-dimensional Generative Foundation Models
Free2Guide: Training-Free Text-to-Video Alignment using Image LVLM
Jaemin Kim, Bryan Sangwoo Kim, Jong Chul Ye ·
ICCV
· 2025
# High-dimensional Generative Foundation Models
VISION-XL: High Definition Video Inverse Problem Solver using Latent Image Diffusion Models
Taesung Kwon, Jong Chul Ye ·
ICCV
· 2025
# High-dimensional Generative Foundation Models
Reangle-A-Video: 4D Video Generation as Video-to-Video Translation
Hyeonho Jeong, Suhyeon Lee, Jong Chul Ye ·
ICCV
· 2025
# Foundation Model for Robotics
Interaction-Merged Motion Planning: Effectively Leveraging Diverse Motion Datasets for Robust Planning
Giwon Lee, Wooseong Jeong, Daehee Park, Jaewoo Jeong, Kuk-Jin Yoon ·
ICCV
· 2025
# Foundation Model for Robotics
DC-TTA: Divide-and-Conquer Framework for Test-Time Adaptation of Interactive Segmentation
Jihun Kim, Hoyong Kwon, Hyeokjun Kweon, Wooseong Jeong, Kuk-Jin Yoon ·
ICCV
· 2025
# Foundation Model for Robotics
Learning Large Motion Estimation from Intermediate Representations with a High-Resolution Optical Flow Dataset Featuring Long-Range Dynamic Motion
Hoonhee Cho, Yuhwan Jeong, Kuk-Jin Yoon ·
ICCV
· 2025
← Prev
1
…
25
26
27
28
29
…
32
Next →