Papers by Cristian-Alexandru Staicu
SimSCOOD: Systematic Analysis of Out-of-Distribution Generalization in Fine-tuned Source Code Models (2024.findings-naacl)
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| Challenge: | Large datasets are increasingly available for pre-training source code models, but obtaining representative training data that fully covers the code distribution for specific downstream tasks remains challenging due to the task-specific nature and limited labeling resources. |
| Approach: | They propose a systematic approach that simulates various OOD scenarios along different dimensions of source code data properties and investigates model behavior under different fine-tuning methodologies. |
| Outcome: | The proposed approach simulates various OOD scenarios along different dimensions of source code data properties and exposes multiple failure modes attributed to OOD generalization issues. |