Jeonghun Cho — accepted AI-conference papers

2025

Retrieval-Augmented Fine-Tuning With Preference Optimization For Visual Program Generation

Deokhyung Kang, Jeonghun Cho, Yejin Jeon, Sunbin Jang, Minsub Lee, Jawoon Cho +1

ACL 2025long

Visual programming languages (VPLs) allow users to create programs through graphical interfaces, which results in easier accessibility and their widespread usage in various domains. To further enhance this accessibility, recent research has focused on generating VPL code from user instructions using…

Cited by 0 Source ↗PDF ↗Scholar ↗

2025

Self-Correcting Code Generation Using Small Language Models

Jeonghun Cho, Deokhyung Kang, Hyounghun Kim, Gary Lee

EMNLP 2025

Self-correction has demonstrated potential in code generation by allowing language models to revise and improve their outputs through successive refinement. Recent studies have explored prompting-based strategies that incorporate verification or feedback loops using proprietary models, as well as tr

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗