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Author

Jungwoo Lee

Observed name: Lee, Jungwoo
ORCID: 0000-0002-6804-980X
Observed ORCID: 0000-0002-6804-980X
OpenAlex ID: A5135418105
Efficient Process Reward Modeling via Contrastive Mutual Information
2026 · Nakyung Lee, Sangwoo Hong, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting · 1
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Learning Rate Transfer for Hybrid Transformer-SSM Architectures
2026 · Seo, Jimin, Lee, Gyubok, et al. · arXiv (Cornell University)
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Training-Free Inference-Budget Reduction in Flow-Matching Vision-Language-Action Models for Robot Manipulation: A Prespecified Evaluation Against a Fixed Task-Success Margin
2026 · Lee, Jungwoo, Lee, Jong-Deuk, et al. · Zenodo (CERN European Organization for Nuclear Research)
Mechanistic Circuit Identification for Controllable Data Generation
2026 · Lee, Nakyung, Hong, Sangwoo, et al. · arXiv (Cornell University)
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A Regret Minimization Framework on Preference Learning in Large Language Models
2026 · Kim, Suhwan, Cho, Taehyun, et al. · arXiv (Cornell University)
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Efficient Process Reward Modeling via Contrastive Mutual Information
2026 · Association for Computational Linguistics 2026, Hong, Sangwoo, et al. · Underline Science Inc.
Counting anticommuting Pauli pairs in linear time
2026 · Cha, Hyunho, Lee, Jungwoo · arXiv (Cornell University)
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Spectral Minimax Direct Fidelity Estimation for Generic Target States
2026 · Cha, Hyunho, Lee, Jungwoo · arXiv (Cornell University)
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Online Estimation of Partial Transpose Moments via Fast Classical Updates
2026 · Cha, Hyunho, Lee, Jungwoo · arXiv (Cornell University)
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Toward the Goldilocks Blind Compression of Quantum States
2026 · Cha, Hyunho, Park, Chae-Yeun, et al. · arXiv (Cornell University)
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Lyapunov-Guided Self-Alignment: Test-Time Adaptation for Offline Safe Reinforcement Learning
2026 · Han, Seungyub, Kim, Hyungjin, et al. · arXiv (Cornell University)
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Optimal dense materialization of the stabilizer formalism without polynomial overhead
2026 · Cha, Hyunho, Lee, Jungwoo · arXiv (Cornell University)
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An Adaptive Sampling Framework for Diffusion-based Dataset Distillation with High Fidelity and Diversity
2026 · Sunbeom Jeong, Sehwan Kim, et al. · Proceedings of the AAAI Conference on Artificial Intelligence
An Adaptive Sampling Framework for Diffusion-based Dataset Distillation with High Fidelity and Diversity
2026 · Association for Artificial Intelligence 2026, Han, Hyeonggeun, et al. · Underline Science Inc.
Bias Alleviation Through Network Pruning for Sparse and Debiased Models
2026 · Sangwoo Hong, Sehwan Kim, et al. · IEEE Transactions on Image Processing
MixTTA: Low-Rank Cross-Channel Mixing for Reliable Test-Time Adaptation
2026 · Mansoo Jung, Youngwook Kim, et al. · Lecture notes in computer science
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Robust Split Federated Offline Reinforcement Learning under Heterogeneous Client Data
2026 · Seungchan Yu, Jungchan Cho, et al. · SSRN Electronic Journal
DCGC: Draft-Conditioned Global Correction for Complex Reasoning with Masked Diffusion Models
2026 · Minhae Oh, Nakyung Lee, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP)
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Towards Understanding Pause Token Fine-Tuning Dynamics: A Mode Retention Perspective
2026 · Jaehyeon Kim, Suhwan Kim, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP)
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Works count: 20
Citation count: 1
H-index: 1
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