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Found 3 papers, 2 papers with code
COMET: Coverage-guided Model Generation For Deep Learning Library Testing
Techniques have been proposed to generate various DL models and apply them to test these libraries.
DeepFD: Automated Fault Diagnosis and Localization for Deep Learning Programs
Besides, for fault localization, DeepFD also outperforms the existing works, correctly locating 42% faulty programs, which almost doubles the best result (23%) achieved by the existing works.
SemMT: A Semantic-based Testing Approach for Machine Translation Systems
SemMT applies round-trip translation and measures the semantic similarity between the original and translated sentences.
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