A review of 114 studies creates taxonomies for code and data quality issues, formalizes 18 propagation mechanisms from training data defects to LLM-generated code defects, and synthesizes detection and mitigation techniques.
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A reduced attention-only decoder shows diminishing returns in dataset scaling, reaching 90% of full accuracy with only 30% of the data.
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Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code
A review of 114 studies creates taxonomies for code and data quality issues, formalizes 18 propagation mechanisms from training data defects to LLM-generated code defects, and synthesizes detection and mitigation techniques.
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Is More Data Worth the Cost? Dataset Scaling Laws in a Tiny Attention-Only Decoder
A reduced attention-only decoder shows diminishing returns in dataset scaling, reaching 90% of full accuracy with only 30% of the data.