Papers by Hyojun Kim
TABS: Efficient Textual Adversarial Attack for Pre-trained NL Code Model Using Semantic Beam Search (2022.emnlp-main)
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| Challenge: | Existing black-box adversarial attacks on pre-trained models generate adversarials with greedy search. |
| Approach: | They propose an efficient beam search black-box adversarial attack method . they use contextual semantic filtering to effectively reduce the search space . |
| Outcome: | The proposed method shows good performance in terms of attack success rate, number of queries, and semantic similarity for two tasks: NL code search classification and retrieval tasks. |
BLOCSUM: Block Scope-based Source Code Summarization via Shared Block Representation (2023.findings-acl)
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| Challenge: | Abstract Syntax Tree (AST) and sequence of code tokens are useful for code summarization. |
| Approach: | They propose a shared block position embedding to represent various code blocks . they also develop variant ASTs to learn rich information such as block and global dependencies . |
| Outcome: | The proposed method improves on two real-world datasets, including ablation studies and a human evaluation. |
SALAD: Improving Robustness and Generalization through Contrastive Learning with Structure-Aware and LLM-Driven Augmented Data (2025.naacl-long)
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| Challenge: | In many natural language processing tasks, model training often leads to spurious correlations . shortcuts allow models to rely on irrelevant patterns in the data, leading to biased predictions. |
| Approach: | They propose a method to generate structure-aware positive and negative sentences using tagging. |
| Outcome: | The proposed method improves model robustness and generalization across different environments while minimizing spurious correlations. |