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Seanie Lee
Seanie Lee
PhD Student, KAIST
Verified email at kaist.ac.kr - Homepage
Title
Cited by
Cited by
Year
Contrastive Learning with Adversarial Perturbations for Conditional Text Generation
S Lee, DB Lee, SJ Hwang
International Conference on Learning Representations, 2021, 2021
1202021
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
742020
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
672018
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
532021
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
462023
Domain-agnostic Question-Answering with Adversarial Training
S Lee, D Kim, J Park
EMNLP MRQA workshop 2019, 2019
442019
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
372020
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
182021
Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning
S Lee, HB Lee, J Lee, SJ Hwang
International Conference on Learning Representations, 2022, 2021
132021
Margin-based Neural Network Watermarking
B Kim, S Lee, S Lee, S Son, SJ Hwang
International Conference on Machine Learning (ICML), 2023, 2023
112023
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
112022
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
92023
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
72024
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
62023
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
62022
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
42024
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
22024
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
22021
Drug Discovery with Dynamic Goal-aware Fragments
S Lee, S Lee, K Kawaguchi, SJ Hwang
International Conference on Machine Learning (ICML), 2024, 2024
12024
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Articles 1–20