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Seanie Lee
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2020 – today
- 2024
- [c20]Dominik Wagner, Seanie Lee, Ilja Baumann, Philipp Seeberger, Korbinian Riedhammer, Tobias Bocklet:
Optimized Speculative Sampling for GPU Hardware Accelerators. EMNLP 2024: 6442-6458 - [c19]Sohyun An, Hayeon Lee, Jaehyeong Jo, Seanie Lee, Sung Ju Hwang:
DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models. ICLR 2024 - [c18]Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang:
Self-Supervised Dataset Distillation for Transfer Learning. ICLR 2024 - [c17]Seul Lee, Seanie Lee, Kenji Kawaguchi, Sung Ju Hwang:
Drug Discovery with Dynamic Goal-aware Fragments. ICML 2024 - [c16]Seanie Lee, Jianpeng Cheng, Joris Driesen, Alexandru Coca, Anders Johannsen:
Effective and Efficient Conversation Retrieval for Dialogue State Tracking with Implicit Text Summaries. NAACL-HLT 2024: 96-111 - [i18]Seanie Lee, Jianpeng Cheng, Joris Driesen, Alexandru Coca, Anders Johannsen:
Effective and Efficient Conversation Retrieval for Dialogue State Tracking with Implicit Text Summaries. CoRR abs/2402.13043 (2024) - [i17]Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain:
Learning diverse attacks on large language models for robust red-teaming and safety tuning. CoRR abs/2405.18540 (2024) - [i16]Dominik Wagner, Seanie Lee, Ilja Baumann, Philipp Seeberger, Korbinian Riedhammer, Tobias Bocklet:
Optimized Speculative Sampling for GPU Hardware Accelerators. CoRR abs/2406.11016 (2024) - [i15]Seanie Lee, Haebin Seong, Dong Bok Lee, Minki Kang, Xiaoyin Chen, Dominik Wagner, Yoshua Bengio, Juho Lee, Sung Ju Hwang:
HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models. CoRR abs/2410.01524 (2024) - 2023
- [c15]Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi:
Self-Distillation for Further Pre-training of Transformers. ICLR 2023 - [c14]Dong Bok Lee, Seanie Lee, Kenji Kawaguchi, Yunji Kim, Jihwan Bang, Jung-Woo Ha, Sung Ju Hwang:
Self-Supervised Set Representation Learning for Unsupervised Meta-Learning. ICLR 2023 - [c13]Byungjoo Kim, Suyoung Lee, Seanie Lee, Sooel Son, Sung Ju Hwang:
Margin-based Neural Network Watermarking. ICML 2023: 16696-16711 - [c12]Jeffrey Willette, Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang:
Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation. ICML 2023: 37008-37041 - [c11]Minki Kang, Seanie Lee, Jinheon Baek, Kenji Kawaguchi, Sung Ju Hwang:
Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks. NeurIPS 2023 - [i14]Sohyun An, Hayeon Lee, Jaehyeong Jo, Seanie Lee, Sung Ju Hwang:
DiffusionNAG: Task-guided Neural Architecture Generation with Diffusion Models. CoRR abs/2305.16943 (2023) - [i13]Minki Kang, Seanie Lee, Jinheon Baek, Kenji Kawaguchi, Sung Ju Hwang:
Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks. CoRR abs/2305.18395 (2023) - [i12]Seul Lee, Seanie Lee, Sung Ju Hwang:
Drug Discovery with Dynamic Goal-aware Fragments. CoRR abs/2310.00841 (2023) - [i11]Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang:
Self-Supervised Dataset Distillation for Transfer Learning. CoRR abs/2310.06511 (2023) - 2022
- [c10]Seanie Lee, Haebeom Lee, Juho Lee, Sung Ju Hwang:
Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning. ICLR 2022 - [c9]Bruno Andreis, Seanie Lee, Tuan A. Nguyen, Juho Lee, Eunho Yang, Sung Ju Hwang:
Set Based Stochastic Subsampling. ICML 2022: 619-638 - [c8]Balhae Kim, Jungwon Choi, Seanie Lee, Yoonho Lee, Jung-Woo Ha, Juho Lee:
On Divergence Measures for Bayesian Pseudocoresets. NeurIPS 2022 - [c7]Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang:
Set-based Meta-Interpolation for Few-Task Meta-Learning. NeurIPS 2022 - [i10]Seanie Lee, Andreis Bruno, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang:
Set-based Meta-Interpolation for Few-Task Meta-Learning. CoRR abs/2205.09990 (2022) - [i9]Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi:
Self-Distillation for Further Pre-training of Transformers. CoRR abs/2210.02871 (2022) - [i8]Balhae Kim, Jungwon Choi, Seanie Lee, Yoonho Lee, Jung-Woo Ha
, Juho Lee:
On Divergence Measures for Bayesian Pseudocoresets. CoRR abs/2210.06205 (2022) - 2021
- [c6]Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang:
Learning to Perturb Word Embeddings for Out-of-distribution QA. ACL/IJCNLP (1) 2021: 5583-5595 - [c5]Seanie Lee, Dong Bok Lee, Sung Ju Hwang:
Contrastive Learning with Adversarial Perturbations for Conditional Text Generation. ICLR 2021 - [c4]Dong Bok Lee, Dongchan Min, Seanie Lee, Sung Ju Hwang:
Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning. ICLR 2021 - [i7]Donggyu Kim, Seanie Lee:
Self-supervised Text-to-SQL Learning with Header Alignment Training. CoRR abs/2103.06402 (2021) - [i6]Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang:
Learning to Perturb Word Embeddings for Out-of-distribution QA. CoRR abs/2105.02692 (2021) - [i5]Seanie Lee, Haebeom Lee, Juho Lee, Sung Ju Hwang:
Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning. CoRR abs/2110.02600 (2021) - 2020
- [c3]Dong Bok Lee, Seanie Lee, Woo Tae Jeong, Donghwan Kim, Sung Ju Hwang:
Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs. ACL 2020: 208-224 - [c2]Kyubyong Park, Seanie Lee:
g2pM: A Neural Grapheme-to-Phoneme Conversion Package for Mandarin Chinese Based on a New Open Benchmark Dataset. INTERSPEECH 2020: 1723-1727 - [i4]Kyubyong Park, Seanie Lee:
g2pM: A Neural Grapheme-to-Phoneme Conversion Package for MandarinChinese Based on a New Open Benchmark Dataset. CoRR abs/2004.03136 (2020) - [i3]Dong Bok Lee, Seanie Lee, Woo Tae Jeong, Donghwan Kim, Sung Ju Hwang:
Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs. CoRR abs/2005.13837 (2020) - [i2]Seanie Lee, Dong Bok Lee, Sung Ju Hwang:
Contrastive Learning with Adversarial Perturbations for Conditional Text Generation. CoRR abs/2012.07280 (2020)
2010 – 2019
- 2019
- [c1]Seanie Lee, Donggyu Kim, Jangwon Park:
Domain-agnostic Question-Answering with Adversarial Training. MRQA@EMNLP 2019: 196-202 - [i1]Seanie Lee, Donggyu Kim, Jangwon Park:
Domain-agnostic Question-Answering with Adversarial Training. CoRR abs/1910.09342 (2019) - 2018
- [j1]Reinald Kim Amplayo, Seanie Lee, Min Song
Incorporating product description to sentiment topic models for improved aspect-based sentiment analysis. Inf. Sci. 454-455: 200-215 (2018)
Coauthor Index
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last updated on 2024-11-15 19:34 CET by the dblp team
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