Papers with real-world LD data

1 papers
Retrieval-Augmented Fine-Tuning With Preference Optimization For Visual Program Generation (2025.acl-long)

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Challenge: Visual programming languages (VPLs) allow users to create programs through graphical interfaces, which results in easier accessibility and widespread usage in various domains.
Approach: They propose to train VPLs from user instructions using large language models . they propose to use retrieval-augmented fine-tuning to leverage repetitive use of subroutines .
Outcome: The proposed method outperforms prompting-based methods for LD generation accuracy even with smaller backbone models.

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