Konkuk University

Trustworthy Machine Learning Lab

AI를 연산부터 실제 물리 세계 구현까지 연구합니다.

Building reliable AI from computing foundations to the physical world.

TML research framework connecting Reliable Computing, Foundation Models, and Physical World with Reliable and Safe AI Algorithms.

Featured Publications

주요 연구 성과

Teaser figure for Efficient Process Reward Modeling via Contrastive Mutual Information
ACL Foundation Models Alignment

Efficient Process Reward Modeling via Contrastive Mutual Information

Nakyung Lee, Sangwoo Hong, Jungwoo Lee

The 64th Annual Meeting of the Association for Computational Linguistics (Main paper), 2026

Paper
Teaser figure for Bias Alleviation through Network Pruning for Sparse and Debiased Models
TIP Foundation Models Fairness

Bias Alleviation through Network Pruning for Sparse and Debiased Models

Sangwoo Hong, Sehwan Kim, Hyungjun Joo, Hyeonggeun Han, Jiyoon Shin, Yoav Wald, and Jungwoo Lee

IEEE Transactions on Image Processing, 2026

Paper
Teaser figure for MVP-LAM: Learning Action-Centric Latent Action via Cross-Viewpoint Reconstruction
ICML Physical World

MVP-LAM: Learning Action-Centric Latent Action via Cross-Viewpoint Reconstruction

Jung Min Lee, Dohyeok Lee, Seokhun Ju, Taehyun Cho, Jin Woo Koo, Li Zhao, Sangwoo Hong, Jungwoo Lee

Proceedings of the 43rd International Conference on Machine Learning, 2026

Paper Code Project

Current Research

현재 진행 중인 연구

Unlearning

Sequential Machine Unlearning

반복적인 정보 삭제에도 모델의 성능을 유지할 수 있을까?

World Models

Shortcut Bias in Autonomous Driving

월드 모델은 실제 세계를 학습하는가, 데이터의 shortcut을 학습하는가?

Multi-Agent Systems

Hallucination Detection

에이전트 간 hallucination은 어떻게 발생하고 전파되는가?

AI for Science

Protein Foundation Models

단백질 모델은 비생물학적 shortcut에 의존하는가?

Quantum Computing

QNG-Accelerated Quantum Optimization

측정과 피드백 비용을 줄여 양자 최적화를 가속할 수 있을까?

Latest News

Recent Updates

Our paper, Function-Level Execution Feedback for Code Preference Optimization, has been accepted to EMNLP 2026 Findings.

Our paper, Geometry-Preserving Robust Neural Reconstruction via Statistical Reweighting, has been accepted to BMVC 2026.

Our team has been selected for the AI Star Fellowship 2026 in collaboration with Jeju National University, NC AI, AIVIS, and Metsakuur. Prof. Hong will serve as Project 2 Leader, focusing on proactive security against multi-unit deepfakes and secure authentication of AI agents. The six-year project has total funding of KRW 11.0 billion.

Our team has been selected to lead a KETI-funded project with access to a cluster of eight NVIDIA B200 GPUs with 1,536 GB total VRAM.

Our team at Konkuk University has been selected for the Group Research Workforce Development Program.

View all news

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