| Contrastive Learning with Adversarial Perturbations for Conditional Text Generation S Lee, DB Lee, SJ Hwang International Conference on Learning Representations, 2021, 2021 | 122 | 2021 |
| Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs DB Lee, S Lee, WT Jeong, D Kim, SJ Hwang Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 75 | 2020 |
| Incorporating product description to sentiment topic models for improved aspect-based sentiment analysis RK Amplayo, S Lee, M Song Information Sciences 454, 200-215, 2018 | 68 | 2018 |
| Meta-GMVAE: Mixture of gaussian vae for unsupervised meta-learning DB Lee, D Min, S Lee, SJ Hwang International Conference on Learning Representations, 2021, 2021 | 53 | 2021 |
| Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks M Kang, S Lee, J Baek, K Kawaguchi, SJ Hwang Advances In Neural Information Processing Systems (NeurIPS), 2023, 2023 | 48 | 2023 |
| Domain-agnostic Question-Answering with Adversarial Training S Lee, D Kim, J Park EMNLP MRQA workshop 2019, 2019 | 45 | 2019 |
| g2pM: A Neural Grapheme-to-Phoneme Conversion Package for Mandarin Chinese Based on a New Open Benchmark Dataset K Park, S Lee INTERSPEECH 2020, 2020 | 37 | 2020 |
| Learning to Perturb Word Embeddings for Out-of-distribution QA S Lee, M Kang, J Lee, SJ Hwang Association for Computational Linguistics (ACL), 5583–5595, 2021 | 19 | 2021 |
| Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning S Lee, HB Lee, J Lee, SJ Hwang International Conference on Learning Representations, 2022, 2021 | 13 | 2021 |
| Margin-based Neural Network Watermarking B Kim, S Lee, S Lee, S Son, SJ Hwang International Conference on Machine Learning (ICML), 2023, 2023 | 11 | 2023 |
| On Divergence Measures for Bayesian Pseudocoresets B Kim, J Choi, S Lee, Y Lee, JW Ha, J Lee Advances In Neural Information Processing Systems (NeurIPS), 2022, 2022 | 11 | 2022 |
| Self-Supervised Set Representation Learning for Unsupervised Meta-Learning DB Lee, S Lee, K Kawaguchi, Y Kim, J Bang, JW Ha, SJ Hwang International Conference on Learning Representations (ICLR), 2023 | 9 | 2023 |
| Learning diverse attacks on large language models for robust red-teaming and safety tuning S Lee, M Kim, L Cherif, D Dobre, J Lee, SJ Hwang, K Kawaguchi, G Gidel, ... arXiv preprint arXiv:2405.18540, 2024 | 7 | 2024 |
| Self-Distillation for Further Pre-training of Transformers S Lee, M Kang, J Lee, SJ Hwang, K Kawaguchi International Conference on Learning Representations (ICLR), 2023 | 7 | 2023 |
| Set-based Meta-Interpolation for Few-Task Meta-Learning S Lee, B Andreis, K Kawaguchi, J Lee, SJ Hwang Advances In Neural Information Processing Systems (NeurIPS), 2022, 2022 | 6 | 2022 |
| DiffusionNAG: Task-guided Neural Architecture Generation with Diffusion Models S An, H Lee, J Jo, S Lee, SJ Hwang International Conference on Learning Representations (ICLR), 2024, 2024 | 4 | 2024 |
| Self-Supervised Dataset Distillation for Transfer Learning DB Lee, S Lee, J Ko, K Kawaguchi, J Lee, SJ Hwang International Conference on Learning Representations (ICLR), 2024, 2024 | 3 | 2024 |
| Drug Discovery with Dynamic Goal-aware Fragments S Lee, S Lee, K Kawaguchi, SJ Hwang International Conference on Machine Learning (ICML), 2024, 2024 | 2 | 2024 |
| Set Based Stochastic Subsampling B Andreis, S Lee, AT Nguyen, J Lee, E Yang, SJ Hwang International Conference on Machine Learning, 619-638, 2022 | 2* | 2022 |
| Self-supervised Text-to-SQL Learning with Header Alignment Training D Kim, S Lee arXiv preprint arXiv:2103.06402, 2021 | 2 | 2021 |
Sung Ju HwangKAIST, DeepAutoVerified email at kaist.ac.kr
