MultiVul uses multimodal contrastive learning to align code and comment representations, yielding up to 27% F1 gains on vulnerability detection benchmarks over prompting and code-only baselines.
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cs.SE 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Proposes a two-stage on-the-fly input adaptation framework to reduce mispredictions in code language models across understanding tasks without retraining or additional supervision.
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Learning Generalizable Multimodal Representations for Software Vulnerability Detection
MultiVul uses multimodal contrastive learning to align code and comment representations, yielding up to 27% F1 gains on vulnerability detection benchmarks over prompting and code-only baselines.
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On-the-Fly Input Adaptation for Reliable Code Intelligence
Proposes a two-stage on-the-fly input adaptation framework to reduce mispredictions in code language models across understanding tasks without retraining or additional supervision.