선도 연구 주제

전체 논문

NAIRL이 세 가지 선도 연구 주제에 걸쳐 발표한 연구의 전체 색인입니다.

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전체 논문

논문 174개
# Breakthrough in Neural Scaling Law

HOT: Hadamard-based Optimized Training

Seonggon Kim, Juncheol Shin, Seung-taek Woo, Eunhyeok Park · CVPR · 2025
# Breakthrough in Neural Scaling Law

Towards Robust and Efficient Federated Low-Rank Adaptation with Heterogeneous Clients

Jabin Koo, Minwoo Jang, Jungseul Ok · ACL · 2025
# Breakthrough in Neural Scaling Law

Semantic Exploration with Adaptive Gating for Efficient Problem Solving with Language Models

Sungjae Lee, Hyejin Park, Jaechang Kim, Jungseul Ok · ACL · 2025
# Breakthrough in Neural Scaling Law

Comparison-based Active Preference Learning for Multi-dimensional Personalization

Minhyeon Oh, Seungjoon Lee, Jungseul Ok · ACL · 2025
# Breakthrough in Neural Scaling Law

LOCALITY-AWARE GAUSSIAN COMPRESSION FOR FAST AND HIGH-QUALITY RENDERING

Seungjoo Shin, Jaesik Park, Sunghyun Cho · ICLR · 2025
# Breakthrough in Neural Scaling Law

Exploiting Deblurring Networks for Radiance Fields

Haeyun Choi, Heemin Yang, Janghyeok Han, Sunghyun Cho · CVPR · 2025
# Breakthrough in Neural Scaling Law

Elevating 3D Models: High-Quality Texture and Geometry Refinement from a Low-Quality Model

Nuri Ryu, Jiyun Won, Jooeun Son, Minsu Gong, Joo-Haeng Lee, Sunghyun Cho · SIGGRAPH · 2025
# Breakthrough in Neural Scaling Law

Review-driven Personalized Preference Reasoning with Large Language Models for Recommendation

Jieyong Kim, Hyunseo Kim, Hyunjin Cho, SeongKu Kang, Buru Chang, Jinyoung Yeo, Dongha Lee · SIGIR · 2025
# Breakthrough in Neural Scaling Law

Blockwise Flow Matching: Improving Flow Matching Models For Efficient High-Quality Generation

Dogyun Park, Taehoon Lee, Minseok Joo, Hyunwoo J. Kim · NeurIPS · 2025
# Breakthrough in Neural Scaling Law

Representation Shift: Unifying Token Compression with FlashAttention

Joonmyung Choi, Sanghyeok Lee, Byungoh Ko, Eunseo Kim, Jihyung Kil, Hyunwoo J. Kim · ICCV · 2025