머신러닝, 학회
ICLR 논문을 낸 국내 연구실
탑티어International Conference on Learning Representations. 2023년 이후 논문 537편, 연구실 205곳
이 학회에 논문을 낸 연구실
| 연구실 | 대학 | 탑티어 논문 | 전체 논문 | 구성원 | 비교 |
|---|---|---|---|---|---|
 Stochastic Dynamics and Machine Learning LabAnh Tong 교수신생 랩 | 고려대 | 3 | 6 | 3 | |
 Ubiquitous AI Lab. 유비쿼터스 인공지능 연구실공태식 교수신생 랩모집 안내 | UNIST | 13 | 21 | 5 | |
 Users and Information Lab오혜연 교수 | KAIST | 33 | 45 | – | |
 Visual Computing and AI (VCAI) Lab문경식 교수신생 랩 | 고려대 | 16 | 18 | 11 | |
 Visual & General Intelligence Lab (시각 및 범용 지능 연구실)박경문 교수모집 안내 | 고려대 | 29 | 39 | – |
최근 논문
- From Assumptions to Actions: Turning LLM Reasoning into Uncertainty-Aware Planning for Embodied Agents
2026, IIIXR Lab
- From Conversation to Query Execution: Benchmarking User and Tool Interactions for EHR Database Agents
2026, 최윤재 연구실
- From Vicious to Virtuous Cycles: Synergistic Representation Learning for Unsupervised Video Object-Centric Learning
2026, 비주얼컴퓨팅 Lab
- GlowQ: Group-Shared LOw-Rank Approximation for Quantized LLMs
2026, Computing for Embedded Lightweight Learning (CELL)
- Graph Signal Processing Meets Mamba2: Adaptive Filter Bank via Delta Modulation
2026, 빅데이터 분석 및 학습 연구실
- Group-Normalized Implicit Value Optimization for Language Models
2026, KAIST AIPR Lab
- HAMLET: Switch Your Vision-Language-Action Model into a History-Aware Policy
2026, AGI-LAB, KAIST
- Harmonized Cone for Feasible and Non-conflict Directions in Training Physics-Informed Neural Networks
2026, MCML
- Harnessing Temporal Databases for Systematic Evaluation of Factual Time-Sensitive Question-Answering in LLMs
2026, 데이터 지능 연구실
- HDR-NSFF: High Dynamic Range Neural Scene Flow Fields
2026, 기계 지능 연구실
- Hierarchical Prototype Learning for Semantic Segmentation
2026, 소프트컴퓨팅
- Hybrid Deep Searcher: Scalable Parallel and Sequential Search Reasoning
2026, 시각 및 학습 연구실
- Identifying Robust Neural Pathways: Few-Shot Adversarial Mask Tuning for Vision-Language Models
2026, 문재균 연구실, Edge AI
- Implicit Bias and Loss of Plasticity in Matrix Completion: Depth Promotes Low-Rankness
2026, 윤철희 연구실
- Implicit Bias of Per-sample Adam on Separable Data: Departure from the Full-batch Regime
2026, 윤철희 연구실
- Improving Black-Box Generative Attacks via Generator Semantic Consistency
2026, KAIST Visual Intelligence Lab
- Improving Discrete Diffusion Unmasking Policies Beyond Explicit Reference Policies
2026, 예종철 연구실
- IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation
2026, 통계적 추론 및 정보 이론 연구실
- Inlier-Centric Post-Training Quantization for Object Detection Models
2026, 통계적 추론 및 정보 이론 연구실
- Instance-Dependent Fixed-Budget Pure Exploration in Reinforcement Learning
2026, Interactive Machine Learning Lab