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2020 – today
- 2024
[c14]Jimin An, YunSeok Choi, Jee-Hyong Lee:
Code Defect Detection Using Pre-trained Language Models with Encoder-Decoder via Line-Level Defect Localization. LREC/COLING 2024: 3446-3456- 2023
- [j3]YunSeok Choi
, CheolWon Na, Hyojun Kim, Jee-Hyong Lee:
READSUM: Retrieval-Augmented Adaptive Transformer for Source Code Summarization. IEEE Access 11: 51155-51165 (2023) - [c13]YunSeok Choi, Jee-Hyong Lee:
CodePrompt: Task-Agnostic Prefix Tuning for Program and Language Generation. ACL (Findings) 2023: 5282-5297 - [c12]CheolWon Na, YunSeok Choi, Jee-Hyong Lee:
DIP: Dead code Insertion based Black-box Attack for Programming Language Model. ACL (1) 2023: 7777-7791 - [c11]YunSeok Choi, Hyojun Kim, Jee-Hyong Lee:
BLOCSUM: Block Scope-based Source Code Summarization via Shared Block Representation. ACL (Findings) 2023: 11427-11441 - [c10]Heeyoon Yang, YunSeok Choi, Gahyung Kim, Jee-Hyong Lee:
LOAM: Improving Long-tail Session-based Recommendation via Niche Walk Augmentation and Tail Session Mixup. SIGIR 2023: 527-536 - 2022
- [c9]YunSeok Choi, Hyojun Kim, Jee-Hyong Lee:
TABS: Efficient Textual Adversarial Attack for Pre-trained NL Code Model Using Semantic Beam Search. EMNLP 2022: 5490-5498 - [c8]Ida Ayu Putu Ari Crisdayanti, JinYeong Bak, YunSeok Choi, Jee-Hyong Lee:
IA-BERT: context-aware sarcasm detection by incorporating incongruity attention layer for feature extraction. SAC 2022: 1084-1091 - 2021
- [c7]YunSeok Choi, JinYeong Bak, CheolWon Na, Jee-Hyong Lee:
Learning Sequential and Structural Information for Source Code Summarization. ACL/IJCNLP (Findings) 2021: 2842-2851 - [c6]Min-Sub Won, YunSeok Choi, Samuel Kim, CheolWon Na, Jee-Hyong Lee:
An embedding method for unseen words considering contextual information and morphological information. SAC 2021: 1055-1062 - 2020
- [j2]YunSeok Choi, Dahae Kim, Jee-Hyong Lee:
Neural attention model with keyword memory for abstractive document summarization. Concurr. Comput. Pract. Exp. 32(18) (2020) - [c5]YunSeok Choi, Suah Kim, Jee-Hyong Lee:
Source Code Summarization Using Attention-Based Keyword Memory Networks. BigComp 2020: 564-570 - [c4]HyunSoo Lee, YunSeok Choi, Jee-Hyong Lee:
Attention history-based attention for abstractive text summarization. SAC 2020: 1075-1081
2010 – 2019
- 2018
- [j1]Noo-Ri Kim, YunSeok Choi, HyunSoo Lee, Jae-Young Choi, Suntae Kim, Jeong-Ah Kim, YoungWha Cho, Jee-Hyong Lee:
Detection of document modification based on deep neural networks. J. Ambient Intell. Humaniz. Comput. 9(4): 1089-1096 (2018) - [c3]YunSeok Choi, Dahae Kim, Jee-Hyong Lee:
Abstractive summarization by neural attention model with document content memory. RACS 2018: 11-16 - 2016
- [c2]Noo-Ri Kim, YunSeok Choi, HyunSoo Lee, Jee-Hyong Lee:
Detection of Content Changes Based on Deep Neural Networks. CSA/CUTE 2016: 806-811 - [c1]YunSeok Choi, Suah Kim, Jee-Hyong Lee:
Recurrent Neural Network for Storytelling. SCIS&ISIS 2016: 841-845
Coauthor Index
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last updated on 2024-08-05 20:20 CEST by the dblp team
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