Lee, Seanie

22 publications

NeurIPS 2025 Distilling LLM Agent into Small Models with Retrieval and Code Tools Minki Kang, Jongwon Jeong, Seanie Lee, Jaewoong Cho, Sung Ju Hwang

NeurIPS 2025 FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA Seanie Lee, Sangwoo Park, Dong Bok Lee, Dominik Wagner, Haebin Seong, Tobias Bocklet, Juho Lee, Sung Ju Hwang

ICLR 2025 HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models Seanie Lee, Haebin Seong, Dong Bok Lee, Minki Kang, Xiaoyin Chen, Dominik Wagner, Yoshua Bengio, Juho Lee, Sung Ju Hwang

ICLR 2025 Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain

NeurIPS 2025 Reliable Decision‑Making via Calibration‑Oriented Retrieval‑Augmented Generation Chaeyun Jang, Deukhwan Cho, Seanie Lee, Hyungi Lee, Juho Lee

NeurIPS 2025 Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training Brian R. Bartoldson, Siddarth Venkatraman, James Diffenderfer, Moksh Jain, Tal Ben-Nun, Seanie Lee, Minsu Kim, Johan Obando-Ceron, Yoshua Bengio, Bhavya Kailkhura

ICLR 2024 DiffusionNAG: Predictor-Guided Neural Architecture Generation with Diffusion Models Sohyun An, Hayeon Lee, Jaehyeong Jo, Seanie Lee, Sung Ju Hwang

ICML 2024 Drug Discovery with Dynamic Goal-Aware Fragments Seul Lee, Seanie Lee, Kenji Kawaguchi, Sung Ju Hwang

ICLRW 2024 Drug Discovery with Dynamic Goal-Aware Fragments Seul Lee, Seanie Lee, Kenji Kawaguchi, Sung Ju Hwang

NeurIPSW 2024 Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain

ICLR 2024 Self-Supervised Dataset Distillation for Transfer Learning Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang

NeurIPS 2023 Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks Minki Kang, Seanie Lee, Jinheon Baek, Kenji Kawaguchi, Sung Ju Hwang

ICML 2023 Margin-Based Neural Network Watermarking Byungjoo Kim, Suyoung Lee, Seanie Lee, Sooel Son, Sung Ju Hwang

ICML 2023 Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation Jeffrey Willette, Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang

ICLR 2023 Self-Distillation for Further Pre-Training of Transformers Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi

ICLR 2023 Self-Supervised Set Representation Learning for Unsupervised Meta-Learning Dong Bok Lee, Seanie Lee, Kenji Kawaguchi, Yunji Kim, Jihwan Bang, Jung-Woo Ha, Sung Ju Hwang

NeurIPS 2022 On Divergence Measures for Bayesian Pseudocoresets Balhae Kim, Jungwon Choi, Seanie Lee, Yoonho Lee, Jung-Woo Ha, Juho Lee

ICLR 2022 Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning Seanie Lee, Hae Beom Lee, Juho Lee, Sung Ju Hwang

ICML 2022 Set Based Stochastic Subsampling Bruno Andreis, Seanie Lee, A. Tuan Nguyen, Juho Lee, Eunho Yang, Sung Ju Hwang

NeurIPS 2022 Set-Based Meta-Interpolation for Few-Task Meta-Learning Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang

ICLR 2021 Contrastive Learning with Adversarial Perturbations for Conditional Text Generation Seanie Lee, Dong Bok Lee, Sung Ju Hwang

ICLR 2021 Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning Dong Bok Lee, Dongchan Min, Seanie Lee, Sung Ju Hwang