Yeachan Kim

According to our database¹, Yeachan Kim authored at least 27 papers between 2018 and 2024.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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PhD thesis

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On csauthors.net:

Bibliography

2024

CleaR: Towards Robust and Generalized Parameter-Efficient Fine-Tuning for Noisy Label Learning.

[BibT_eX]

[DOI]

Yeachan Kim

Junho Kim

SangKeun Lee

CoRR, 2024

C2A: Client-Customized Adaptation for Parameter-Efficient Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Moleco: Molecular Contrastive Learning with Chemical Language Models for Molecular Property Prediction.

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: EMNLP 2024, 2024

Zero-shot Commonsense Reasoning over Machine Imagination.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

MolTRES: Improving Chemical Language Representation Learning for Molecular Property Prediction.

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

SEED: Semantic Knowledge Transfer for Language Model Adaptation to Materials Science.

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: EMNLP 2024, 2024

MELT: Materials-aware Continued Pre-training for Language Model Adaptation to Materials Science.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

KOMBO: Korean Character Representations Based on the Combination Rules of Subcharacters.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Towards Robust and Generalized Parameter-Efficient Fine-Tuning for Noisy Label Learning.

[BibT_eX]

[DOI]

Yeachan Kim

Junho Kim

SangKeun Lee

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

SparseFlow: Accelerating Transformers by Sparsifying Information Flows.

[BibT_eX]

[DOI]

Yeachan Kim

SangKeun Lee

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Learning From Drift: Federated Learning on Non-IID Data via Drift Regularization.

[BibT_eX]

[DOI]

Yeachan Kim

Bonggun Shin

CoRR, 2023

Phase-shifted adversarial training.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Leap-of-Thought: Accelerating Transformers via Dynamic Token Routing.

[BibT_eX]

[DOI]

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Improving Bias Mitigation through Bias Experts in Natural Language Understanding.

[BibT_eX]

[DOI]

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Client-Customized Adaptation for Parameter-Efficient Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Dynamic Structure Pruning for Compressing CNNs.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Context-based Virtual Adversarial Training for Text Classification with Noisy Labels.

[BibT_eX]

[DOI]

Do-Myoung Lee

Yeachan Kim

Chang-gyun Seo

Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

In Defense of Core-set: A Density-aware Core-set Selection for Active Learning.

[BibT_eX]

[DOI]

Yeachan Kim

Bonggun Shin

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

An Interpretable Framework for Drug-Target Interaction with Gated Cross Attention.

[BibT_eX]

[DOI]

Yeachan Kim

Bonggun Shin

Proceedings of the Machine Learning for Healthcare Conference, 2021

2020

Personalizing large-scale text classification by modeling individual differences.

[BibT_eX]

[DOI]

Proceedings of the SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing, online event, [Brno, Czech Republic], March 30, 2020

Representation Learning for Unseen Words by Bridging Subwords to Semantic Networks.

[BibT_eX]

[DOI]

Yeachan Kim

Kang-Min Kim

SangKeun Lee

Proceedings of The 12th Language Resources and Evaluation Conference, 2020

Multi-pretraining for Large-scale Text Classification.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Adaptive Compression of Word Embeddings.

[BibT_eX]

[DOI]

Yeachan Kim

Kang-Min Kim

SangKeun Lee

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

From Small-scale to Large-scale Text Classification.

[BibT_eX]

[DOI]

Proceedings of the World Wide Web Conference, 2019

2018

Learning to Generate Word Representations using Subword Information.

[BibT_eX]

[DOI]

Proceedings of the 27th International Conference on Computational Linguistics, 2018

A Unified Approach to Word Sense Representation and Disambiguation.

[BibT_eX]

[DOI]

Proceedings of the 17th IEEE International Conference on Cognitive Informatics & Cognitive Computing, 2018

Improving Open Directory Project-Based Text Classification with Hierarchical Category Embedding.

[BibT_eX]

[DOI]

Proceedings of the 17th IEEE International Conference on Cognitive Informatics & Cognitive Computing, 2018

Yeachan Kim

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