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Limitations of Synthetic Data Generation in Specialized Data-Scarce Domains
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data augmentationgenerative modelsclassificationdata scarcity
2608.13729
Builder Relevance
1h ago30%
Abstract
This paper evaluates the effectiveness of synthetic data generation in specialized, data-scarce domains, revealing limitations in performance compared to non-generative methods.
Reality Card
Core Claim
No generative approach consistently outperforms a strong non-generative baseline in trauma classification tasks.
Method / Result
Across five trauma classification tasks, generative methods did not yield performance improvements over non-generative baselines.
Limitations
Recurring failure modes include memorization or collapse, distributional drift, and generation of visually plausible but simplified instances.
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