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ORCIDYeachan Kim
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2020 – today
- 2024
[c24]SungHo Kim, Juhyeong Park, Yeachan Kim, SangKeun Lee:
KOMBO: Korean Character Representations Based on the Combination Rules of Subcharacters. ACL (Findings) 2024: 5102-5119- [c23]Yeachan Kim, Junho Kim, SangKeun Lee:
Towards Robust and Generalized Parameter-Efficient Fine-Tuning for Noisy Label Learning. ACL (1) 2024: 5922-5936 - [c22]Yeachan Kim, SangKeun Lee:
SparseFlow: Accelerating Transformers by Sparsifying Information Flows. ACL (1) 2024: 5937-5948 - [c21]Jun-Hyung Park, Hyuntae Park, Yeachan Kim, Woosang Lim, SangKeun Lee:
Moleco: Molecular Contrastive Learning with Chemical Language Models for Molecular Property Prediction. EMNLP (Industry Track) 2024: 408-420 - [c20]Yeachan Kim, Jun-Hyung Park, SungHo Kim, Juhyeong Park, Sangyun Kim, SangKeun Lee:
SEED: Semantic Knowledge Transfer for Language Model Adaptation to Materials Science. EMNLP (Industry Track) 2024: 421-428 - [c19]Junho Kim, Yeachan Kim, Jun-Hyung Park, Yerim Oh, Suho Kim, SangKeun Lee:
MELT: Materials-aware Continued Pre-training for Language Model Adaptation to Materials Science. EMNLP (Findings) 2024: 10690-10703 - [c18]Hyuntae Park, Yeachan Kim, Jun-Hyung Park, SangKeun Lee:
Zero-shot Commonsense Reasoning over Machine Imagination. EMNLP (Findings) 2024: 11451-11471 - [c17]Jun-Hyung Park, Yeachan Kim, Mingyu Lee, Hyuntae Park, SangKeun Lee:
MolTRES: Improving Chemical Language Representation Learning for Molecular Property Prediction. EMNLP 2024: 14241-14254 - [i12]Jun-Hyung Park, Yeachan Kim, Mingyu Lee, Hyuntae Park, SangKeun Lee:
MolTRES: Improving Chemical Language Representation Learning for Molecular Property Prediction. CoRR abs/2408.01426 (2024) - [i11]Hyuntae Park, Yeachan Kim, Jun-Hyung Park, SangKeun Lee:
Zero-shot Commonsense Reasoning over Machine Imagination. CoRR abs/2410.09329 (2024) - [i10]Junho Kim, Yeachan Kim, Jun-Hyung Park, Yerim Oh, Suho Kim, SangKeun Lee:
MELT: Materials-aware Continued Pre-training for Language Model Adaptation to Materials Science. CoRR abs/2410.15126 (2024) - [i9]Yeachan Kim, Junho Kim, Wing-Lam Mok, Jun-Hyung Park, SangKeun Lee:
C2A: Client-Customized Adaptation for Parameter-Efficient Federated Learning. CoRR abs/2411.00311 (2024) - [i8]Yeachan Kim, Junho Kim, SangKeun Lee:
CleaR: Towards Robust and Generalized Parameter-Efficient Fine-Tuning for Noisy Label Learning. CoRR abs/2411.00873 (2024) - 2023
- [c16]Jun-Hyung Park, Yeachan Kim, Junho Kim, Joon-Young Choi, SangKeun Lee:
Dynamic Structure Pruning for Compressing CNNs. AAAI 2023: 9408-9416 - [c15]Yeachan Kim, Junho Kim, Wing-Lam Mok, Jun-Hyung Park, SangKeun Lee:
Client-Customized Adaptation for Parameter-Efficient Federated Learning. ACL (Findings) 2023: 1159-1172 - [c14]Eojin Jeon, Mingyu Lee
, Juhyeong Park, Yeachan Kim, Wing-Lam Mok, SangKeun Lee:
Improving Bias Mitigation through Bias Experts in Natural Language Understanding. EMNLP 2023: 11053-11066 - [c13]Yeachan Kim, Junho Kim, Jun-Hyung Park, Mingyu Lee, SangKeun Lee:
Leap-of-Thought: Accelerating Transformers via Dynamic Token Routing. EMNLP 2023: 15757-15769 - [c12]Yeachan Kim, Seongyeon Kim, Ihyeok Seo, Bonggun Shin:
Phase-shifted adversarial training. UAI 2023: 1068-1077 - [i7]Yeachan Kim, Seongyeon Kim, Ihyeok Seo, Bonggun Shin:
Phase-shifted Adversarial Training. CoRR abs/2301.04785 (2023) - [i6]Jun-Hyung Park, Yeachan Kim, Junho Kim, Joon-Young Choi, SangKeun Lee:
Dynamic Structure Pruning for Compressing CNNs. CoRR abs/2303.09736 (2023) - [i5]Yeachan Kim, Bonggun Shin:
Learning From Drift: Federated Learning on Non-IID Data via Drift Regularization. CoRR abs/2309.07189 (2023) - [i4]Eojin Jeon, Mingyu Lee, Juhyeong Park, Yeachan Kim, Wing-Lam Mok, SangKeun Lee:
Improving Bias Mitigation through Bias Experts in Natural Language Understanding. CoRR abs/2312.03577 (2023) - 2022
- [c11]Yeachan Kim, Bonggun Shin:
In Defense of Core-set: A Density-aware Core-set Selection for Active Learning. KDD 2022: 804-812 - [c10]Do-Myoung Lee, Yeachan Kim, Chang-gyun Seo:
Context-based Virtual Adversarial Training for Text Classification with Noisy Labels. LREC 2022: 6139-6146 - [i3]Yeachan Kim, Bonggun Shin:
In Defense of Core-set: A Density-aware Core-set Selection for Active Learning. CoRR abs/2206.04838 (2022) - [i2]Do-Myoung Lee, Yeachan Kim, Chang-gyun Seo:
Context-based Virtual Adversarial Training for Text Classification with Noisy Labels. CoRR abs/2206.11851 (2022) - 2021
- [c9]Yeachan Kim, Bonggun Shin:
An Interpretable Framework for Drug-Target Interaction with Gated Cross Attention. MLHC 2021: 337-353 - [i1]Yeachan Kim, Bonggun Shin:
An Interpretable Framework for Drug-Target Interaction with Gated Cross Attention. CoRR abs/2109.08360 (2021) - 2020
- [c8]Yeachan Kim, Kang-Min Kim, SangKeun Lee:
Adaptive Compression of Word Embeddings. ACL 2020: 3950-3959 - [c7]Kang-Min Kim, Bumsu Hyeon, Yeachan Kim, Jun-Hyung Park, SangKeun Lee:
Multi-pretraining for Large-scale Text Classification. EMNLP (Findings) 2020: 2041-2050 - [c6]Yeachan Kim, Kang-Min Kim, SangKeun Lee:
Representation Learning for Unseen Words by Bridging Subwords to Semantic Networks. LREC 2020: 4774-4780 - [c5]Jungho Lee, Byung-Ju Choi, Yeachan Kim, Kang-Min Kim, Woo-Jong Ryu, SangKeun Lee:
Personalizing large-scale text classification by modeling individual differences. SAC 2020: 900-902
2010 – 2019
- 2019
- [c4]Kang-Min Kim, Yeachan Kim, Jungho Lee, Ji-Min Lee, SangKeun Lee:
From Small-scale to Large-scale Text Classification. WWW 2019: 853-862 - 2018
- [c3]Ji-Min Lee, Kang-Min Kim, Yeachan Kim, SangKeun Lee:
Improving Open Directory Project-Based Text Classification with Hierarchical Category Embedding. ICCI*CC 2018: 246-253 - [c2]Do-Myoung Lee, Yeachan Kim, Ji-Min Lee, SangKeun Lee:
A Unified Approach to Word Sense Representation and Disambiguation. ICCI*CC 2018: 330-336 - [c1]Yeachan Kim, Kang-Min Kim, Ji-Min Lee, SangKeun Lee:
Learning to Generate Word Representations using Subword Information. COLING 2018: 2551-2561
Coauthor Index
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